Computing platform for facilitating data exchange among computing environments

Information

  • Patent Grant
  • 12153704
  • Patent Number
    12,153,704
  • Date Filed
    Thursday, August 4, 2022
    2 years ago
  • Date Issued
    Tuesday, November 26, 2024
    26 days ago
Abstract
Various aspects of the disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for facilitating the exchange of data among a diverse group of first and third party computing environments. Accordingly, various aspects of the disclosure provide a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. In some aspects, the data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data.
Description
TECHNICAL FIELD

The present disclosure is generally related to systems and methods for processing data requests involving exchange of data between computing environments while protecting the data from maliciously caused destruction, unauthorized modification, or unauthorized disclosure.


BACKGROUND

A significant challenge encountered by many entities such as organizations, corporations, companies, and/or the like is mitigating risks associated with integrating computer-related functionality provided by third party computing systems (e.g., software, storage, processing capacity, etc.). For example, a first party may integrate computer-related functionality provided through a third party computing system into a computing system of the first party in the form of a computer-implemented service provided by the third party computing system that interfaces with the first party computing system. In another example, the first party may integrate computer-related functionality provided through the third party computing system into the first party computing system in the form of software functionality provided by the third party computing system that is installed within the first party computing system. Such integrations can expose the first party computing system to signification risk of experiencing some type of incident such as a data security breach, unauthorized access to the first party computing system, malicious attacks on the first party computing system such as malware or ransomware, and/or the like.


To combat this challenge, many first parties will vet the integration of computer-related functionality provided by third party computing systems into first party computing systems to evaluate the risk associated with such integrations and to better understand what challenges may be involved in such integrations. Often, the vetting process involves gathering data (e.g., information) from third parties that are associated with these third party computing systems. For example, a first party may request a third party to complete an assessment to provide information on particular computer-related functionality provided through a third party computing system so that the first party can use such information in performing the vetting process.


However, the data gathering process can present significant technical challenges to many first and third parties. For instance, technical challenges can arise from the fact that the different first parties and third parties that can be involved in the data gathering process may be quite diverse with respect to computing environments in which they operate and the different functionality, capabilities, interfaces, and/or the like among the computing environments. This diversity among the computing environments can often create significant diversity in the way in which these different computing environments communicate and exchange data. Therefore, any particular first or third party may be required to operate their computing environment using a variety of hardware components and/or software components, providing a variety of functionality, capabilities, and/or the like, so that the particular first or third party can take part in the data gathering process with a large number of other first and/or third parties.


In addition, technical challenges can arise due to the number of third parties any one first party may need to gather data from, as well as the volume of data that may need to be gathered from these third parties. The same can be true with respect to the number of first parties any one third party may need to provide data to, as well as the volume of data that may need to be provided to these first parties. For example, the data gathering process can prove to be quite taxiing on a first or third party's computing environment due to a large number of data requests and/or a large amount of data that may be involved in the data gathering process, as well as a large number of first and/or third party computing environments that needs to be interacted with in fulfilling the data requests.


Further, technical challenges can arise due to requirements imposed by first and/or third parties to allow exchange of certain types of data. For example, a third party may require a particular type of data that is considered to be sensitive in nature to be managed with certain security and/or access controls in place. These security and/or access controls can prove to be quite challenging when they need to be implemented within a first party's computing environment so that the computing environment is sufficiently operated to be used in the data gathering process. This can be especially true when the first party may be dealing with multiple third parties who impose different, conflicting requirements that need to be implemented within the first party's computing environment. Accordingly, a need exists in the art for improved systems and methods for facilitating data exchange among a diverse group of first and third computing environments. Various aspects of the disclosure provided herein address such a need.


SUMMARY

In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for exchanging data among computing environments. In accordance with various aspects, a method is provided that comprises: receiving, by computing hardware, a request on behalf of a first party to have a third party provide an electronic artifact, wherein: the request is submitted by the first party through a data exchange computing platform, the data exchange computing platform provides a data exchange service that facilitates exchange of electronic artifacts between a plurality of tenants of the data exchange computing platform, and the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform; determining, by the computing hardware, that the third party is not a tenant of the plurality of tenants; responsive to determining the third party is not the tenant of the plurality of tenants, sending, by the computing hardware, an electronic notification on behalf of the first party to the third party requesting the electronic artifact, wherein the electronic notification comprises an invitation mechanism for facilitating registration of the third party with the data exchange service; receiving, by the computing hardware, an indication of an activation of the invitation mechanism; and responsive to receiving the indication: generating, by the computing hardware, a second tenant instance on the data exchange computing platform for the third party to facilitate the third party being a second tenant of the plurality of tenants; and providing, by the computing hardware, access to the request via the second tenant instance so that the request is automatically available to the third party through the data exchange service.


In some aspects, the method further comprises: providing, by the computing hardware, an upload mechanism through the second tenant instance to facilitate the third party uploading the electronic artifact into the data exchange computing platform; receiving, by the computing hardware and via the upload mechanism, the electronic artifact; and responsive to receiving the electronic artifact: providing, by the computing hardware, access to the electronic artifact to the first party through the first tenant instance; and sending, by the computing hardware, a second electronic notification to the first party indicating the electronic artifact is available through the data exchange service.


In some aspects, the electronic artifact comprises an assessment to be completed by the third party and the method further comprises: providing, by the computing hardware, an access mechanism through the second tenant instance to facilitate the third party accessing the assessment via the data exchange service; receiving, by the computing hardware, a second indication of a second activation of the access mechanism; responsive to receiving the second indication, providing, by the computing hardware, access to the assessment through the second tenant instance; providing, by the computing hardware, an upload mechanism through the second tenant instance to facilitate the third party uploading a completed version of the assessment into the data exchange computing platform; receiving, by the computing hardware and via the upload mechanism, the completed version of the assessment; and responsive to receiving the completed version of the assessment: providing, by the computing hardware, access to the completed version of the assessment to the first party through the first tenant instance; and sending, by the computing hardware, a second electronic notification to the first party indicating the completed version of the assessment is available through the data exchange service.


In some aspects, providing the upload mechanism through the second tenant instance to facilitate the third party uploading the completed version of the assessment into the data exchange computing platform comprises: providing, by the computing hardware, access to autocompletion assessment software through the second tenant instance, wherein the assessment comprises a set of questions and the autocompletion assessment software is configured to automatically identify answers to the set of questions based on previous answers to previous questions provided by the third party in a previous assessment completed by the third party; and processing, by the computing hardware, the assessment using the autocompletion assessment software to identify an answer to at least one question of the set of questions and to load the answer to the at least one question into the assessment as part of generating the completed version of the assessment. In some aspects, generating the second tenant instance on the data exchange computing platform for the third party to facilitate the third party being the second tenant of the plurality of tenants comprises: sending, by the computing hardware, a second electronic communication comprising a conformation mechanism for confirming creation of the second tenant instance for the third party; receiving, by the computing hardware, a second indication of an activation of the conformation mechanism; and responsive to receiving the second indication, creating, by the computing hardware, the second tenant instance on the data exchange computing platform.


In some aspects, the method further comprises: receiving, by the computing hardware and via the second tenant instance, a second request to claim a third party trust profile, wherein the third party trust profile is configured for allowing the third party to manage availability of the electronic artifacts through the data exchange service to the plurality of tenants; and responsive to receiving the second request: locking, by the computing hardware, the third party trust profile so that the third party trust profile is unavailable to be claimed by another tenant of the plurality of tenants; submitting, by the computing hardware, the second request to claim the third party trust profile to be validated; receiving, by the computing hardware, a second indication that the second request to claim the third party trust profile has been validated; and responsive to receiving the second indication, linking the third party trust profile to the second tenant instance in the data exchange computing platform so that the third party trust profile is available to the third party through the second tenant instance.


In some aspects, the method further comprises: receiving, by the computing hardware and via the second tenant instance, a third request to post a particular electronic artifact to the third party trust profile; receiving, by the computing hardware, the particular electronic artifact uploaded through the second tenant instance by the third party; and posting, by the computing hardware, the particular electronic artifact to the third party trust profile so that the particular electronic artifact is publicly available to the plurality of tenants.


In some aspects, the method further comprises: receiving, by the computing hardware and via the second tenant instance, a third request to post a particular electronic artifact to the third party trust profile; receiving, by the computing hardware, the particular electronic artifact uploaded through the second tenant instance by the third party; posting, by the computing hardware, the particular electronic artifact to the third party trust profile so that the particular electronic artifact is privately available to the plurality of tenants; receiving, by the computing hardware and from a particular tenant of the plurality of tenants, a fourth request to access the particular electronic artifact; and responsive to receiving the fourth request: sending, by the computing hardware, a second electronic communication to the third party, wherein the second electronic communication comprises the fourth request to access the particular electronic artifact; receiving, by the computing hardware, a third indication to fulfill the fourth request; and responsive to receiving the third indication, providing, by the computing hardware, access to the particular electronic artifact through a tenant instance associated with the particular tenant.


In accordance with various aspects, a system is provided comprising a non-transitory computer-readable medium storing instructions and a processing device communicatively coupled to the non-transitory computer-readable medium. The processing device is configured to execute the instructions and thereby perform operations comprising: receiving a request on behalf of a first party to have a third party provide an electronic artifact, wherein: the request is submitted by the first party through a data exchange computing platform used in facilitating exchange of electronic artifacts between a plurality of tenants of the data exchange computing platform; and the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform; sending an electronic notification on behalf of the first party to the third party requesting the electronic artifact, wherein the electronic notification comprises an invitation mechanism for facilitating the third party become a second tenant of the plurality of tenants; receiving an indication of an activation of the invitation mechanism; and responsive to receiving the indication: generating a second tenant instance on the data exchange computing platform for the third party to facilitate the third party being the second tenant of the plurality of tenants; and providing access to the request via the second tenant instance so that the request is automatically available to the third party through the data exchange computing platform.


In some aspects, the operations further comprise: receiving, via an upload mechanism, the electronic artifact, wherein the upload mechanism is provided through the second tenant instance; and responsive to receiving the electronic artifact, providing access to the electronic artifact to the first party through the first tenant instance. In some aspects, the electronic artifact comprises an assessment to be completed by the third party and the operations further comprise: providing access to the assessment through the second tenant instance; providing an upload mechanism through the second tenant instance to facilitate uploading a completed version of the assessment into the data exchange computing platform; receiving, via the upload mechanism, the completed version of the assessment; and providing access to the completed version of the assessment through the first tenant instance. In some aspects, providing the upload mechanism through the second tenant instance comprises: providing access to autocompletion assessment software through the second tenant instance, wherein the assessment comprises a set of questions and the autocompletion assessment software is configured to automatically identify answers to the set of questions based on previous answers to previous questions provided in a previous assessment completed by the third party; and processing the assessment using the autocompletion assessment software to identify an answer to at least one question of the set of questions and to load the answer to the at least one question into the assessment as part of generating the completed version of the assessment.


In some aspects, generating the second tenant instance on the data exchange computing platform for the third party comprises: receiving a second indication of an activation of a conformation mechanism provided in a second electronic communication; and responsive to receiving the second indication, creating the second tenant instance on the data exchange computing platform. In some aspects, the operations further comprise: receiving, via the second tenant instance, a second request to claim a third party trust profile, wherein the third party trust profile is configured for allowing managing availability of the electronic artifacts through the data exchange computing platform to the plurality of tenants; responsive to receiving the second request, locking the third party trust profile so that the third party trust profile is unavailable to be claimed by another tenant of the plurality of tenants; submitting the second request to claim the third party trust profile to be validated; receiving a second indication that the second request to claim the third party trust profile has been validated; and responsive to receiving the second indication, linking the third party trust profile to the second tenant instance in the data exchange computing platform.


In some aspects, the operations further comprise: receiving a particular electronic artifact uploaded through the second tenant instance to post to the third party trust profile; and posting the particular electronic artifact to the third party trust profile so that the particular electronic artifact is publicly available to at least a subset of the plurality of tenants. In some aspects, the operations further comprise: receiving a particular electronic artifact uploaded through the second tenant instance to post to the third party trust profile; posting the particular electronic artifact to the third party trust profile; receiving, from a particular tenant of the plurality of tenants, a third request to access the particular electronic artifact; and responsive to receiving the third request: sending a second electronic communication, wherein the second electronic communication comprises the third request to access the particular electronic artifact; receiving a third indication to fulfill the third request; and responsive to receiving the third indication, providing access to the particular electronic artifact through a tenant instance associated with the particular tenant.


In accordance with various aspects, a non-transitory computer-readable medium is provided having computer-executable instructions that are stored thereon. The instructions that, when executed by computing hardware, configure the computing hardware to perform operations comprising: receiving a request on behalf of a first party to have a third party provide data, wherein: the request is submitted through a data exchange computing platform used in facilitating exchange of data between a plurality of tenants of the data exchange computing platform; and the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform; receiving an indication to generate a second tenant instance for the third party, wherein the indication is generated as a result of the third party being notified of the request; and responsive to receiving the indication: generating the second tenant instance on the data exchange computing platform for the third party to facilitate the third party being a second tenant of the plurality of tenants; and providing access to the request via the second tenant instance so that the request is available to the third party through the data exchange computing platform.


In some aspects, the operations further comprise: sending an electronic notification on behalf of the first party to the third party notifying the third party of the request for the data, wherein the electronic notification comprises an invitation mechanism and the indication is received as a result of an activation of the invitation mechanism. In some aspects, the operations further comprise: receiving the data via an upload mechanism provided through the second tenant instance; and responsive to receiving the data, providing access to the data to the first party through the first tenant instance. In some aspects, the operations further comprise: receiving, via the second tenant instance, a second request to claim a third party trust profile, wherein the third party trust profile is configured for allowing managing availability of data through the data exchange computing platform to the plurality of tenants; and responsive to receiving the second request, locking the third party trust profile so that the third party trust profile is unavailable to be claimed by another tenant of the plurality of tenants; submitting the second request to claim the third party trust profile to be validated; receiving a second indication that the second request to claim the third party trust profile has been validated; and responsive to receiving the second indication, linking the third party trust profile to the second tenant instance in the data exchange computing platform.


In accordance with various aspects, a method is provided that comprises: sending, by computing hardware, an electronic notification on behalf of a first party to a third party requesting completion of an electronic assessment, wherein: the electronic notification comprises an access mechanism for facilitating access to the electronic assessment and is sent via a data exchange computing platform, the data exchange computing platform provides a data exchange service that facilitates exchange of data between a plurality of tenants of the data exchange computing platform, and the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform; receiving, by the computing hardware, a first indication of an activation of the access mechanism; responsive to receiving the first indication, providing, by the computing hardware, a graphical user interface for display, wherein the graphical user interface comprises a control element configured for facilitating registration of the third party with the data exchange service; receiving, by the computing hardware, a second indication of an activation of the control element; and responsive to receiving the second indication: generating, by the computing hardware, a second tenant instance on the data exchange computing platform for the third party to facilitate the third party being a second tenant of the plurality of tenants; and providing, by the computing hardware, access to autocompletion assessment software through the data exchange service, wherein the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party so that the electronic assessment can be submitted to the first party through the data exchange computing platform.


In some aspects, the electronic assessment comprises a set of questions and the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party by: comparing each question of the set of questions to each previous question of a set of previous questions found in an answer library, wherein the answer library comprises a corresponding previous answer for each previous question of the set of previous questions provided by the third party for a previous electronic assessment completed by the third party; identifying, based on comparing each question of the set of questions to each previous question of the set of previous questions, an answer to at least one question of the set of questions, wherein the answer comprises the corresponding previous answer for a previous question of the set of previous questions; and populating the answer to the at least one question in the electronic assessment as part of generating a completed version of the electronic assessment.


In some aspects, the electronic notification identifies the autocompletion assessment software is available through the data exchange service. In some aspects, the method further comprises receiving, by the computing hardware via the data exchange computing platform, a request that involves requesting completion of the electronic assessment by the third party, wherein the request is submitted by the first party through the data exchange service and identifies the electronic assessment and the third party. In some aspects, the graphical user interface further comprises a validation control element and the method further comprises, prior to generating the second tenant instance on the data exchange computing platform: receiving, by the computing hardware via the validation control element, input; and validating, by the computing hardware and based on the input, that the activation of the access mechanism is associated with the third party.


In some aspects, the method of claim 1 further comprises: sending, by the computing hardware, a second electronic notification comprising a conformation mechanism for confirming creation of the second tenant instance for the third party; and receiving, by the computing hardware, a third indication of an activation of the conformation mechanism, wherein the second tenant instance is generated based on receiving the third indication. In some aspects, the method of claim 1 further comprises: receiving, by the computing hardware via the data exchange computing platform, a request from the first party for an artifact from the third party, wherein the request is submitted by the first party through the first tenant instance; responsive to receiving the request: sending, by the computing hardware, a second electronic notification to the third party, wherein the second electronic notification identifies the request; and providing, by the computing hardware, access to the request to the third party through the second tenant instance; receiving, by the computing hardware, the artifact uploaded into the data exchange computing platform by the third party through the second tenant instance; and responsive to receiving the artifact: sending, by the computing hardware, a third electronic notification to the first party, wherein the third electronic notification identifies the artifact is available through the data exchange service; and providing, by the computing hardware, access to the artifact to the first party through the first tenant instance.


In accordance with various aspects, a system is provided comprising a non-transitory computer-readable medium storing instructions and a processing device communicatively coupled to the non-transitory computer-readable medium. The processing device is configured to execute the instructions and thereby perform operations comprising: sending an electronic notification on behalf of a first party to a third party requesting completion of an electronic assessment, wherein: the electronic notification is sent through a data exchange computing platform, the data exchange computing platform facilitates exchange of data between a plurality of tenants of the data exchange computing platform, the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform, and the electronic notification comprises an invitation mechanism for facilitating registration of the third party with the data exchange computing platform and indicates autocompletion assessment software is available through the data exchange computing platform; receiving a first indication of an activation of the invitation mechanism; responsive to receiving the first indication, providing a graphical user interface for display, wherein the graphical user interface comprises a control element configured for facilitating registration of the third party with the data exchange computing platform; receiving a second indication of an activation of the control element; and responsive to receiving the second indication: generating a second tenant instance on the data exchange computing platform to facilitate the third party being a second tenant of the plurality of tenants; and providing the third party with access to the autocompletion assessment software through the second tenant instance, wherein the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party so that the electronic assessment can be submitted to the first party through the data exchange computing platform.


In some aspects, the electronic assessment comprises a set of questions and the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party by: comparing each question of the set of questions to each previous question found in a set of previous question/previous answer pairings, wherein each previous answer of the set of previous question/previous answer pairings was provided by the third party for a previous assessment completed by the third party; identifying, based on comparing each question of the set of questions to each previous question of the set of previous question/previous answer pairings, an answer to at least one question of the set of questions, wherein the answer comprises the previous answer for one previous question/previous answer pairing of the set of previous question/previous answer pairings; and populating the electronic assessment with the answer to the at least one question.


In some aspects, the operations further comprise receiving, via the data exchange computing platform, a request that involves requesting completion of the electronic assessment by the third party, wherein the request is submitted by the first party through the first tenant instance and identifies the electronic assessment and the third party. In some aspects, the graphical user interface further comprises a validation control element and the operations further comprise, prior to generating the second tenant instance on the data exchange computing platform: receiving, via the validation control element, input; and validating, based on the input, that the activation of the invitation mechanism is associated with the third party. In some aspects, the operations further comprise: sending a second electronic notification comprising a conformation mechanism for confirming creation of the second tenant instance for the third party; and receiving a third indication of an activation of the conformation mechanism, wherein the second tenant instance is generated based on receiving the third indication.


In some aspects, the operations further comprise: receiving a request from the first party for an artifact from the third party; responsive to receiving the request, sending a second electronic notification to the third party, wherein the second electronic notification identifies the request; receiving the artifact uploaded into the data exchange computing platform by the third party through the second tenant instance; and responsive to receiving the artifact: sending a third electronic notification to the first party, wherein the third electronic notification identifies the artifact is available; and providing access to the artifact to the first party through the first tenant instance. In some aspects, the operations further comprise linking a third party trust profile to the second tenant instance in the data exchange computing platform so that the third party trust profile is available to the third party through the second tenant instance, wherein the third party trust profile is configured for allowing the third party to manage availability of data through the data exchange computing platform to the plurality of tenants. In some aspects, the operations further comprise: receiving particular data uploaded through the second tenant instance by the third party; and posting the particular data to the third party trust profile so that the particular data is publicly available to the plurality of tenants.


In accordance with various aspects, a non-transitory computer-readable medium is provided having computer-executable instructions that are stored thereon. The instructions that, when executed by computing hardware, configure the computing hardware to perform operations comprising: sending an electronic notification on behalf of a first party to a third party requesting completion of an electronic assessment, wherein: the electronic notification is sent through a data exchange computing platform, the data exchange computing platform facilitates exchange of data between a plurality of tenants of the data exchange computing platform, the first party is a first tenant of the plurality of tenants and has a first tenant instance on the data exchange computing platform, and the electronic notification comprises an invitation mechanism for facilitating registration of the third party with the data exchange computing platform; receiving a first indication of an activation of the invitation mechanism; responsive to receiving the first indication, providing a graphical user interface for display, wherein the graphical user interface comprises a control element configured for facilitating registration of the third party with the data exchange computing platform; receiving a second indication of an activation of the control element; and responsive to receiving the second indication: generating a second tenant instance on the data exchange computing platform to facilitate the third party being a second tenant of the plurality of tenants; and providing the third party with access to autocompletion assessment software through the second tenant instance, wherein the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party.


In some aspects, the electronic assessment comprises a set of questions and the autocompletion assessment software is configured for automatically completing the electronic assessment for the third party by: comparing each question of the set of questions to each previous question found in a set of previous question/previous answer pairings, wherein each previous answer of the set of previous question/previous answer pairings was provided by the third party for a previous assessment completed by the third party; identifying, based on comparing each question of the set of questions to each previous question of the set of previous question/previous answer pairings, an answer to at least one question of the set of questions, wherein the answer comprises the previous answer for one previous question/previous answer pairing of the set of previous question/previous answer pairings; and populating the electronic assessment with the answer to the at least one question.


In some aspects, the graphical user interface further comprises a validation control element and the operations further comprise, prior to generating the second tenant instance on the data exchange computing platform: receiving, via the validation control element, input; and validating, based on the input, that the activation of the invitation mechanism is associated with the third party. In some aspects, the operations further comprise: receiving a request from the first party for particular data from the third party; responsive to receiving the request, sending a second electronic notification to the third party, wherein the second electronic notification identifies the request; receiving the particular data uploaded into the data exchange computing platform by the third party through the second tenant instance; and responsive to receiving the particular data: sending a third electronic notification to the first party, wherein the third electronic notification identifies the particular data is available; and providing access to the particular data to the first party through the first tenant instance. In some aspects, the operations further comprise linking a third party trust profile to the second tenant instance in the data exchange computing platform so that the third party trust profile is available to the third party through the second tenant instance, wherein the third party trust profile is configured for allowing the third party to manage availability of data through the data exchange computing platform to the plurality of tenants.


In accordance with various aspects, a method is provided that comprises: receiving, by computing hardware, an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions; performing, by the computing hardware, a tokenization technique on the set of questions to generate a first token representation of each question in the set of questions; identifying, by the computing hardware and based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein: the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, and the first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on a similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question; generating, by the computing hardware and based on a level of the similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question, a first confidence measure, wherein the first confidence measure identifies a confidence in the first answer being correct for the first question; providing, by the computing hardware, a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question and the first confidence measure; receiving, by the computing hardware and via the graphical user interface, an indication that the first answer is correct for the first question; and responsive to receiving the indication, populating, by the computing hardware, the electronic assessment with the first answer for the first question.


In some aspects, the method further comprises: receiving, by the computing hardware, a first input of a first location of the set of questions found in the electronic assessment; receiving, by the computing hardware, a second input of a second location of answers to provide for the set of questions in the electronic assessment; identifying, by the computing hardware and based on the first location and the second location, a position in the electronic assessment for providing each answer for each question in the set of questions; and generating, by the computing hardware, a mapping comprising the position in the electronic assessment for providing each answer for each question in the set of questions, wherein populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer. In some aspects, the method further comprises: extracting, by the computing hardware and based on the first location and the second location, each question in the set of questions from the electronic assessment.


In some aspects, the method further comprises: receiving, by the computing hardware, a selection of the answer library from a set of answer libraries available for the entity. In some aspects, the method further comprises: receiving, by the computing hardware, the at least one previous electronic assessment; extracting, by the computing hardware, the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment; performing, by the computing hardware, the tokenization technique on the set of previous questions to generate the second token representation of each previous question in the set of previous questions; and generating, by the computing hardware, the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions.


In some aspects, the method further comprises: identifying, by the computing hardware and based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; generating, by the computing hardware and based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question; providing, by the computing hardware, the second answer to the second question and the second confidence measure for display on the graphical user interface; receiving, by the computing hardware and via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; and responsive to receiving the corrected answer, populating, by the computing hardware, the electronic assessment with the corrected answer for the second question. In some aspects, the method further comprises updating, by the computing hardware, the answer library to include the corrected answer for the second previous question.


In some aspects, the method further comprises: identifying, by the computing hardware and based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; generating, by the computing hardware and based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question; providing, by the computing hardware, the second answer to the second question and the second confidence measure for display on the graphical user interface; receiving, by the computing hardware and via the graphical user interface, a second indication that the second answer is incorrect for the second question; and responsive to receiving the second indication, updating, by the computing hardware, the answer library to include the second question.


In accordance with various aspects, a system is provided comprising a non-transitory computer-readable medium storing instructions and a processing device communicatively coupled to the non-transitory computer-readable medium. The processing device is configured to execute the instructions and thereby perform operations comprising: receiving an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions; performing a tokenization technique on the set of questions to generate a first token representation of each question in the set of questions; identifying, based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein: the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, and the first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on a similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question; providing a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question; receiving, via the graphical user interface, an indication that the first answer is correct for the first question; and responsive to receiving the indication, populating the electronic assessment with the first answer for the first question.


In some aspects, the operations further comprise: receiving a first input of a first location of the set of questions found in the electronic assessment; receiving a second input of a second location of answers to provide for the set of questions in the electronic assessment; and generating a mapping comprising a position in the electronic assessment for providing each answer for each question in the set of questions, wherein: the position is based on the first location and the second location, and populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer. In some aspects, the operations further comprise extracting each question in the set of questions from the electronic assessment based on the first location and the second location.


In some aspects, the operations further comprise: extracting the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment; performing the tokenization technique on the set of previous questions to generate the second token representation of each previous question in the set of previous questions; and generating the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions. In some aspects, the operations further comprise: identifying, based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; providing the second answer to the second question for display on the graphical user interface; receiving, via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; and responsive to receiving the corrected answer, populating the electronic assessment with the corrected answer for the second question. In some aspects, the operations further comprise updating the answer library to include the corrected answer for the second previous question.


In some aspects, the operations further comprise: identifying, based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; providing the second answer to the second question for display on the graphical user interface; receiving, via the graphical user interface, a second indication that the second answer is incorrect for the second question; and responsive to receiving the second indication, updating the answer library to include the second question.


In accordance with various aspects, a non-transitory computer-readable medium is provided having computer-executable instructions that are stored thereon. The instructions that, when executed by computing hardware, configure the computing hardware to perform operations comprising: receiving an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions; generating a first token representation of each question in the set of questions; identifying, based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein: the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, and the first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on the corresponding second token representation for the first previous question and the corresponding first token representation for the first question; providing a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question; receiving, via the graphical user interface, an indication that the first answer is correct for the first question; and responsive to receiving the indication, populating the electronic assessment with the first answer for the first question.


In some aspects, the operations further comprise: receiving a first input of a first location of the set of questions found in the electronic assessment; receiving a second input of a second location of answers to provide for the set of questions in the electronic assessment; generating a mapping comprising a position in the electronic assessment for providing each answer for each question in the set of questions, wherein: the position is based on the first location and the second location, and populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer. In some aspects, the operations further comprise: extracting the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment; generating the second token representation of each previous question in the set of previous questions; and generating the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions.


In some aspects, the operations further comprise: identifying, based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; providing the second answer to the second question for display on the graphical user interface; receiving, via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; and responsive to receiving the corrected answer: populating the electronic assessment with the corrected answer for the second question; and updating the answer library to include the corrected answer for the second previous question. In some aspects, the operations further comprise: identifying, based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on the corresponding second token representation for the second previous question and the corresponding first token representation for the second question; providing the second answer to the second question for display on the graphical user interface; receiving, via the graphical user interface, a second indication that the second answer is incorrect for the second question; and responsive to receiving the second indication, updating the answer library to include the second question.





BRIEF DESCRIPTION OF THE DRAWINGS

In the course of this description, reference will be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:



FIG. 1 depicts an example of a computational configuration that can be involved in facilitating data exchange among a diverse group of first and third party computing environments according to various aspects of the present disclosure;



FIG. 2 depicts an example of a process for processing an artifact request in accordance with various aspects of the present disclosure;



FIG. 3 depicts an example of a process for fulfilling an artifact request in accordance with various aspects of the present disclosure;



FIG. 4 depicts an example of a process for autocompleting an electronic assessment in accordance with various aspects of the present disclosure;



FIG. 5 depicts an example of a process for ingesting an electronic assessment in accordance with various aspects of the present disclosure;



FIG. 6 depicts an example of a process for identifying answers to questions in accordance with various aspects of the present disclosure;



FIG. 7 depicts an example of a process for populating answers in an electronic assessment in accordance with various aspects of the present disclosure;



FIGS. 8A and 8B depict an example of a process for registering a third party with a data exchange service in accordance with various aspects of the present disclosure;



FIG. 9 depicts an example of a process for linking a trust profile to a third party tenant instance in accordance with various aspects of the present disclosure;



FIG. 10 depicts an example of a system architecture that may be used in accordance with various aspects of the present disclosure; and



FIG. 11 depicts an example of a computing entity that may be used in accordance with various aspects of the present disclosure.





DETAILED DESCRIPTION

Overview


As noted, a significant challenge encountered by many entities (e.g., first parties) such as organizations, corporations, companies, and/or the like is mitigating risks associated with integrating computer-related functionality provided by third party computing systems (e.g., computer-related services, software, storage, processing capacity, etc.). To combat this challenge, many first parties will vet the integration of computer-related functionality provided by third party computing systems into computing systems of the first parties (e.g., first party computing systems) to evaluate the risk associated with such integrations and to better understand what challenges may be involved in such integrations. Often, the vetting process involves gathering data (e.g., information) from third parties that are associated with these third party computing systems. For example, a first party may request a third party to complete an assessment to provide information on particular computer-related functionality provided through a third party computing system so that the first party can use such information in performing the vetting process. In another example, a first party may request a third party to provide supporting documentation with respect to some aspect of the computer-related functionality. Accordingly, the first party may request various types of data from the third party and a particular piece of data such as an assessment, document, certification, and/or the like requested by a first party may be referred to as an “artifact.” In this respect, a third party may (continuously) receive multiple data requests from multiple first parties for multiple types of artifacts.


However, the data gathering process can present significant technical challenges to many first and/or third parties. For instance, technical challenges can arise from the fact that the different first parties and third parties that can be involved in the data gathering process may be quite diverse with respect to computing environments in which they operate and the different functionality, capabilities, interfaces, and/or the like among the computing environments. For example, a computing environment for a particular third party (e.g., a particular third party computing environment) may be required to interact with multiple first party computing environments to fulfill requests for various artifacts from the multiple first party computing environments. The multiple first party computing environments may use different hardware components and/or software components in providing communication channels to facilitate data exchange with external computing environments. Therefore, the particular third party computing environment may be required to have functionality and/or capabilities in place to interface, communicate, and/or the like with these different hardware components and/or software components.


Such technical challenges can arise even though some of first and/or third parties may be willing to use more standardized communication channels, such as email, to help facilitate exchange of artifacts. First, standardized communication channels used within many computing environments are typically accessible (available) to a large number of individuals (e.g., “users”) of the environments. Therefore, the use of standardized communication channels can cause the data gathering process to become decentralized in nature because too many individuals can become easily involved in the data gathering process with artifacts being freely exchanged through the standardized communication channels between multiple individuals who are associated with various first and/or third parties.


This exchange can often occur without proper controls in place to ensure data requests are being timely fulfilled, and that the proper (correct) artifacts are being provided in the exchange. In addition, this exchange can often occur with the individuals who are involved in the exchange not knowing whether other individuals have already fulfilled the data requests and/or what artifacts have already been exchanged. Thus, the use of standardized communication channels within first and third party computing environments to facilitate exchange of artifacts during the data gathering process can result in inefficiencies in the use of various resources found in these environments due to the decentralized nature caused by the use of such channels.


Second, even though some first and/or third parties may be comfortable with using standardized communication channels, many other first and/or third parties are not. Often these first and/or third parties will require some other type of, more secure, communication channel be used in exchanging an artifact. For example, this may be because the artifact may be considered sensitive in nature. Or in the alternative, some of these first and/or third parties may be willing to use more standardized communication channels, but may require that such channels be used with additional security features and/or functionality such as encryption. Accordingly, many first and/or third parties may be required to implement hardware components and/or software components within their computing environments to facilitate these more secure communication channels required by several different first and/or third parties. This can prove to be technically challenging, as well create inefficiencies within their computing environments. Thus, the diversity found among the computing environments of various first and third parties can make exchanging data between the computing environments of these parties exceedingly difficult.


In addition, technical challenges can arise due to the number of third parties any one first party may need to gather data from, as well as the volume of data (e.g., number of artifacts) that may need to be gathered from these third parties. The same can be true for a third party with respect to the number of first parties any one third party may need to provide data to, as well as the volume of data (e.g., number of artifacts) that may need to be provided to these first parties.


More specifically, the data gathering process can prove to be quite taxiing on a first party's and/or third party's computing environment due to a large number of first and/or third party computing environments that needs to be interacted with and/or the amount of data that needs to be collected and/or provided. For example, a first party may be looking to implement certain computer-functionality into a computing system. Here, the first party may be vetting several different third parties in deciding which of the third parties' computer-related functionality to implement into the first party's computing system. In addition, the first party may require several different artifacts from each third party in performing the vetting process. Therefore, the first party's computing environment needs to interact with several different computing environments of the various third parties during the data gathering process to collect the different artifacts from each of the third parties.


The same can hold true for a third party who is required to fulfill data requests received from several different first parties. The third party's computing environment needs to interact with several different computing environments of the various first parties during the data gathering process to provide the different artifacts to each of the first parties. Not only can this prove technically challenging with respect to the first or third party's computing environment interacting with a diverse group of first and/or third party computing environments, but this can also prove technically challenging to the first or third party computing environment with respect to the resources required in facilitating the data gathering process involving the diverse group of first and/or third party computing environments.


Further, technical challenges can arise due to requirements imposed by first and/or third parties to allow exchange of certain types of data (e.g., exchange of certain artifacts). For example, a third party may require a particular artifact that is considered to be sensitive in nature to be handled with certain security and/or access controls in place. These security and/or access controls can prove to be quite challenging when they need to be implemented within a first party's computing environment so that the computing environment is sufficiently operated and can be used in the data gathering process. This can be especially true when the first party may be dealing with multiple third parties who impose different, conflicting requirements that need to be implemented within the first party's computing environment. Accordingly, the data gathering process can present significant technical challenges to many first and/or third parties.


Various aspects of the present disclosure overcome many of the technical challenges associated with facilitating data exchange among a diverse group of first and third party computing environments as discussed herein. Specifically, various aspects are directed to a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. The data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data. These various first and third parties register with the data exchange service to become tenants of the service and as a result, tenant instances are generated on the data exchange computing platform for the various first and third parties.


In various aspects, the data exchange computing platform provides a centralized, uniform, and secure environment in which the various first and third parties can exchange data (e.g., artifacts) among themselves through their computing environments. Therefore, the data exchange computing platform can address many of the technical challenges that result from different first and third parties being involved in the data gathering process who have diverse computing environments in which they operate and the different functionality, capabilities, interfaces, and/or the like among the diverse computing environments. Here, the data exchange computing platform can serve as a single, uniform, and secure point (e.g., interface) through which a computing environment for a particular first or third party can interact with to exchange data with multiple, diverse computing environments of other first and/or third parties, without the concerns of having to implement a diverse set of functionality, capabilities, interfaces, and/or the like in order to exchange the data with the multiple, diverse computing environments.


It is noted that any particular entity can be a first party or a third party, depending on the data exchange taking place. For example, a first particular entity may be interested in using a computer-implemented service provided by a second particular entity. Here, the first particular entity may require one or more artifacts from the second particular entity in evaluating whether or not to use the computer-implemented service, which may interface with a computing system of the first particular party. In this instance, the first particular entity is serving in a first party role of the data exchange, while the second particular entity is serving in a third party role of the data exchange.


However, the same first particular entity may also provide a computer-implemented service. A third particular entity may be interested in evaluating the computer-implemented service that is to interface with a computing system of the third particular entity and the third particular entity may request one or more artifacts from the first particular entity in conducting the evaluation of the computer-implemented service. In this instance, the first particular entity is serving in a third party role of the data exchange, while the third particular entity is serving in a first party role of the data exchange. Thus, the data exchange computing platform can address many of the technical challenges that result from the first particular entity serving in either a first party or third party role with the first particular entity's computing environment interacting with the diversity found in both second and third entities' computing environments.


In various aspects, each tenant instance on the data exchange computing platform provides the corresponding first or third party with a portal though which the first or third party can access the data exchange service to initiate and/or fulfill requests for data sent to and/or received from other first and/or third parties who are also tenants of the data exchange service. Accordingly, the data exchange computing platform can allow for a first party to send a request for data (e.g., a particular artifact) through the first party's tenant instance directly to a third party who is also a tenant of the data exchange service. In turn, the data exchange computing platform can allow for a third party to fulfill a request for data through the third party's tenant instance directly with a first party who is also a tenant of the data exchange service.


In some aspects, the data exchange computing platform can allow for a first party to send a request for data (e.g., a particular artifact) through the first party's tenant instance to a third party who is not currently a tenant of the data exchange service. For example, the data exchange computing platform can receive the request and determine that the third party is not a tenant of data exchange service. As a result, the data exchange computing platform can send an electronic notification, such as an email, on behalf of the first party to the third party (e.g., personnel thereof) requesting the data. Here, the electronic notification can include an invitation mechanism for facilitating registration of the third party with the data exchange service. For example, the invitation mechanism can be a hyperlink that when activated, opens a guest portal (e.g., graphical user interface) for the data exchange service in a browser application residing on a user device being used by the personnel. In some aspects, the guest portal may include a control element configured for facilitating registration of the third party with the data exchange service. Therefore, upon activation of the control element, the data exchange computing platform can generate a tenant instance on the data exchange computing platform for the third party to facilitate the third party becoming a tenant of the data exchange service.


In addition, the data exchange computing platform can provide access to the request received from the first party via the third party's tenant instance so that the request is automatically available to the third party through the data exchange service. Further, the data exchange computing platform can provide an upload mechanism through the third party's tenant instance to facilitate the third party uploading the requested data into the data exchange computing platform. Upon receiving the uploaded data, the data exchange computing platform can then provide access to the data to the first party through the first party's tenant instance. In addition, the data exchange computing platform can send an electronic notification to the first party indicating the data is available through the data exchange service.


Accordingly, the data exchange computing platform can facilitate the exchange of the data between the first and third parties without concern of the functionality, capabilities, interfaces, and/or the like of the first and third parties' computing environments. In other words, the data exchange computing platform can address the technical challenges that can result from a diverse group of computing environments that may be found among the different first and/or third parties in that the data exchange computing platform can provide a centralized, uniform, and secure environment in which the various first and third parties can exchange data.


In some instances, a first party may submit a request that involves an artifact such as an electronic assessment that the first party wishes to have the third party complete. For example, the electronic assessment may involve a set of questions that the first party may request the third party to answer, and the first party may provide the electronic assessment to complete. The data exchange computing platform can provide the third party with access to the electronic assessment through the third party's tenant instance. In addition, the data exchange computing platform can provide an upload mechanism through the third party's tenant instance to facilitate the third party uploading a completed version of the electronic assessment into the data exchange computing platform. Upon receiving the completed version of the electronic assessment, the data exchange computing platform can provide access to the completed version of the electronic assessment to the first party through the first party's tenant instance. In addition, the data exchange computing platform can send an electronic notification to the first party indicating the completed version of the electronic assessment is available through the data exchange service. Accordingly, the data exchange computing platform can facilitate the completion of an electronic assessment by the third party without concern of the functionality, capabilities, interfaces, and/or the like of the first and third parties' computing environments.


In various aspects, the data exchange computing platform provides autocompletion assessment software through the data exchange service to assist third parties with completing electronic assessments requested by first parties. The autocompletion assessment software is configured to automatically identify answers to the set of questions found in the electronic assessment based on previous answers to previous questions provided by the third party in one or more previous electronic assessments completed by the third party. The autocompletion assessment software can then load the answers into the electronic assessment as part of generating the completed version of the electronic assessment.


In some aspects, the autocompletion assessment software may use an answer library generated for the third party that includes a set of previous questions answered by the third party for at least one previous electronic assessment, a token representation for each previous question in the set of previous questions, and at least one previous answer for each previous question in the set of previous questions. Accordingly, the data exchange computing platform can execute the autocompletion assessment software to perform natural language processing on the set of questions found in the electronic assessment to generate a token representation of each question. The software can then identify, based on the answer library, at least one answer to any particular question in the set of questions. Here, the answer comprises the one or more corresponding previous answers for a previous question in the set of previous questions based on a similarity between the corresponding token representation for the previous question and the corresponding token representation for the particular question. In addition, the software can generate, based on a level of the similarity between the corresponding tokens, a confidence measure that identifies a confidence in the answer being correct for the corresponding question.


The data exchange computing platform can further execute the autocompletion assessment software to provide a graphical user interface that displays the answers identified for the questions and their confidence measures. The confidence measures can allow for personnel of the third party to more quickly review the answers for correctness by concentrating on those answers that have a lower confidence measure. The graphical user interface can allow for the personnel to correct/revise any answers and/or to identify those answers that may be wrong for the corresponding questions. The data exchange computing platform can then update the answer library accordingly. For example, the data exchange computing platform can update the answer library to reflect a corrected/revised answer for a particular question. In addition, the data exchange computing platform can revise the token representation in the answer library for any previous question in which the previous question was mistakenly identified by the autocompletion assessment software as corresponding to a question found in the electronic assessment.


The data exchange computing platform can further execute the autocompletion assessment software to populate the electronic assessment with the answers for questions found in the assessment that have been identified as correct by the personnel. In some aspects, the autocompletion assessment software is configured to generate a mapping of the set of questions found in the electronic assessment, and more specifically generate a mapping of the positions in the electronic assessment where the answers to the various questions are to be filled in for the electronic assessment. The autocompletion assessment software can then use this mapping in populating the answers in the electronic assessment to generate a completed version of the electronic assessment. Therefore, the autocompletion assessment software can assist third parties in completing electronic assessments more quickly, as well as assist the third parties in providing accurate and consistent answers to the set of questions provided in the electronic assessments. Such capabilities can be especially beneficial to third parties who may receive a significant number of electronic assessments from different first parties.


In various aspects, the data exchange computing platform also provides third party trust profiles to further assist third parties with providing first parties with access to data (e.g., various type of artifacts) of the third parties. A third party trust profile can serve as an electronic forum available through the data exchange service that is controlled by a particular (associated) third party with respect to making data available through the third party trust profile. For example, the third party trust profile can be used in publicly publishing data (e.g., artifacts) to make the data available to other tenants of the data exchange service. In addition, the third party trust profile can be used in privately publishing data (e.g., artifacts) to make the data available to a select group of tenants of the data exchange service. Further, the third party trust profile can be used in facilitating receipt of requests for data, as well as fulfilling requests for data. Furthermore, the third party trust profile can be used in providing other data on the third party such as information on various computer-related functionality (e.g., services and/or products) offered by the third party, certifications held by the third party, endorsements received by the third party, case studies conducted by the third party, and/or the like.


In various aspects, the data exchange computing platform facilitates a third party claiming a third party trust profile. Here, the data exchange computing platform can receive a request from a third party to claim a particular third party trust profile and in response, lock the third party trust profile so that the profile becomes unavailable to be claimed by another third party (e.g., another tenant of the data exchange service). The data exchange computing platform then submits the request to claim the particular third party trust profile to be validated.


In some aspects, the data exchange computing platform validates the request without human intervention, or with minimal human intervention. For example, the request may include data (information) on the third party and/or personnel (e.g., an individual) who is submitting the request that can then be used by the data exchange computing platform to validate the request for the third party trust profile. As a specific example, the data may include identification information on personnel (e.g., the individual) who submitted the request on behalf of the third party. Here, the data exchange computing platform may use the identification information to investigate publicly available information found through various data sources (e.g., information found on LinkedIn®) to determine that the request is legitimate and that the proper third party (and/or personnel thereof) is claiming the third party trust profile. In other aspects, the data exchange computing platform submits the request to validation personnel who then conducts a validation process to validate that the request is legitimate.


The data exchange computing platform can receive an indication that the request to claim the particular third party trust profile has been validated. In turn, the data exchange computing platform can link the third party trust profile to the third party's tenant instance in the data exchange computing platform so that the third party trust profile is available to the third party through the third party's tenant instance (e.g., portal thereof). At this point, the third party (e.g., personnel thereof) can access the third party trust profile and control the availability of data provided through the third party trust profile.


Accordingly, the third party trust profile can address many of the technical challenges the third party may encounter with respect to the diversity that can be experienced in fulfilling data requests with respect to first parties' computing environments in which they operate and the different functionality, capabilities, interfaces, and/or the like among the computing environments. In addition, the third party trust profile can address many of the technical challenges the third party may encounter that can arise due to the number of first parties the third party may need to provide data to, as well as the volume of data (e.g., number of artifacts) that may need to be provided to these first parties. The third party trust profile can facilitate the exchange of data with first parties without the third party's computing environment necessarily having to directly interact with the first parties' computing environment. In some instances, the third party trust profile can facilitate the exchange of data without the third party having to necessarily get involved at all in the request for the data. For example, the data involved in a request may be publicly available through the third party's trust profile. As a result, the third party trust profile can reduce the number of requests for data received from first parties that the third party may need to field. Accordingly, other technical contributions of various aspects of the disclosure will become apparent in further details of these various aspects provided herein.


Example Computational Configuration



FIG. 1 depicts an example of a computational configuration that can be involved in facilitating data exchange among a diverse group of first and third party computing environments 170, 180 according to various aspects. A data exchange computing platform 100 is provided that may contain the integration of one or more computing systems to facilitate the exchange of data between the first and third party computing environments 170, 180. Accordingly, a computing system of the data exchange computing platform 100 can include various software components and/or hardware components used in facilitating the exchange of data between the first and third party computing environments 170, 180.


For example, a first party may be looking to integrate computer-related functionality provided by a computing system 182 found within a third party's computing environment 180 into a computing system 172 found within the first party's computing environment 170. Here, the first party may be interested in vetting the integration of the computer-related functionality to evaluate the risk associated with the integration and to better understand what challenges may be involved in the integration. Therefore, the first party may require certain data (e.g., certain artifacts) from the third party to use in the vetting process.


Accordingly, the data exchange computing platform 100 in various aspects can facilitate exchange of the certain data between the first and third parties by providing a data exchange service that is accessible over one or more networks 160 (e.g., the Internet) by the first and third parties who are “tenants” of the data exchange service. The data exchange computing platform 100 can provide personnel of the first and third parties with portals that are accessible over the one or more networks 160 by a first party tenant computing system 171 for the first party and a third party tenant computing system 181 for the third party. For example, the portals can comprise one or more graphical user interfaces (e.g., one or more webpages) that are provided through the data exchange service and are used in accessing tenant instances found on the data exchange computing platform 100 for the first and third parties.


The tenant instances provide the first and third parties (e.g., personnel thereof) with various functionality that can be performed within the data exchange service to facilitate exchanging data between the first and third parties over the data exchange computing platform 100. For example, the first party's tenant instance can facilitate the first party's submission of a request for certain data from the third party. In turn, the third party's tenant instance can facilitate fulfilling the request and providing the first party with the certain data. In facilitating this exchange of data, the tenant instances for the first and third parties can allow for personnel of the third party to upload the certain data from the third party tenant computing system 181 into the data exchange computing platform 100. The tenant instances can then provide personnel of the first party with access to the certain data uploaded to the data exchange computing platform 100 from the first party tenant computing system 171. Accordingly, the data exchange computing platform 100 can facilitate this exchange of data without the first party's computing environment 170 having to directly interact with the third party's computing environment 180.


The data exchange computing platform 100 in various aspects includes a repository 150 that can be used for storing data (e.g., various artifacts) that has been uploaded by different third parties to make the data more readily available through the data exchange service. For example, the repository 150 can be used in storing data for a particular third party that can then be made available through the third party's trust profile. Therefore, the repository 150 can serve as a centralized, secure source of data for the third party that can then be used in fulfilling data requests, as well as making data publicly available through the third party's trust profile to other tenants of the data exchange service.


In some aspects, the data exchange computing platform 100 executes an artifact request module 110 that processes a request for particular data (e.g., a particular artifact) submitted by a first party to have fulfilled by a third party. The artifact request module 110 first identifies whether the third party being asked to fulfill the request is a current tenant of the data exchange service. If so, then the artifact request module 110 processes the request to make the request available through the third party's tenant instance. The data exchange computing platform 100 can then provide the third party with access to the request and allow the third party to fulfill the request through the third party's tenant instance. If the third party is not a current tenant of the data exchange service, then the artifact request module 110 can facilitate sending an invitation to the third party to register with the data exchange service and become a tenant of the service. Once registered, the data exchange computing platform 100 can provide the third party with access to the request and allow the third party to fulfill the request through the tenant instance generated on the data exchange computing platform 100 for the third party.


In additional or alternative aspects, the data exchange computing platform 100 executes a process request link module 115. The process request link module 115 processes a request for data that has been responded to by the third party. The data exchange computing platform 100 can send an electronic notification, such as an email, to the third party (e.g., personnel thereof) on behalf of a first party identifying a request for data has been made by the first party. The notification can include an access mechanism that the third party can activate to access the data exchange service and invoke the process request link module 115. In turn, the process request link module 115 directs the third party to the third party's portal that provides access to the third party's tenant instance. The process request link module 115 can then provide the third party with access to the request through the third party's tenant instance, as well as an upload mechanism to allow the third party to upload the requested data into the data exchange computing platform 100. In addition, in instances where the data involves an artifact such as an electronic assessment, the process request link module 115 can provide the third party with access to the assessment, itself, through the third party's tenant instance. Once the data is uploaded, the process request link module 115 can make the uploaded data available to the first party who requested the data through the first party's tenant instance. In addition, the process request link module 115 can save the uploaded data to the repository 150 for the third party.


In additional or alternative aspects, the data exchange computing platform 100 provides autocompletion assessment software within the data exchange service that can be used by a third party in completing an electronic assessment. Accordingly, the autocompletion assessment software can include an autocompletion assessment module 120, an ingest module 125, an identify answers module 130, and a populate assessment module 135. The data exchange computing platform 100 executes the autocompletion assessment module 120 to assist a third party in completing an electronic assessment that has been submitted by a first party for completion by the third party. The autocompletion assessment module 120 assists the third party by automatically identifying answers to the questions provided in electronic assessment and loading the identified answers into the assessment.


In assisting the third party, the autocompletion invokes the ingest module 125, the identify answers module 130, and populate assessment module 135. The data exchange computing platform 100 executes the ingest module 125 to extract the set of questions found in the electronic assessment and ingest them into the data exchange computing platform 100 so that each question in the set of questions can be processed for identifying one or more appropriate answers for the question.


The data exchange computing platform 100 executes the identify answers module 130 to identify appropriate answers for one or more questions found in the set of questions. Here, the identify answers module 130 identifies the answers by comparing the questions found in the set of questions to previous questions answered by the third party in one or more previous assessments completed by the third party. In some aspects, the data exchange computing platform 100 can generate one or more answer libraries for the third party that include previous questions and answers provided in the one or more previous assessments completed by the third party. The identify answers module 130 can then use these answer libraries in identifying appropriate answers to questions found in the electronic assessment.


The data exchange computing platform 100 executes the populate assessment module 135 to populate the electronic assessment with the identified answers for various questions found in the set of questions presented in the assessment. In various aspects, the populate assessment module 135 makes use of a mapping generated for the set of questions presented in the electronic assessment that identifies positions found in the assessment where the answers to the set of questions are to be provided. Accordingly, the populate assessment module 135 can use the mapping in automatically populating the electronic assessment with the identified answers to one or more of the set of questions to generate a completed version of the electronic assessment.


In additional or alternative aspects, when the data exchange computing platform 100 receives a request for data from a third party who is not currently a tenant of the data exchange service, the data exchange computing platform 100 executes a process invitation link module 140 to process an invitation sent to the third party to become a tenant of the data exchange service. The data exchange computing platform 100 can send an electronic notification, such as an email, to the third party (e.g., personnel thereof) on behalf of a first party notifying the third party that the first party is requesting data from the third party and inviting the third party to register with the data exchange service. The notification can include an invitation mechanism that the third party can activate to register with the data exchange service. In turn, the process invitation link module 140 directs the third party (e.g., personnel thereof) to a guest portal that facilitates the third party's registration with the data exchange service. For example, the guest portal can comprise one or more graphical user interfaces (e.g., one or more webpages) that facilitates the third party's registration with the data exchange service.


The process invitation link module 140 validates the registration for the third party and once validated, creates a tenant instance on the data exchange computing platform 100 for the third party. In addition, the process invitation link module 140 can confirm the registration of the third party. Once confirmed, the process invitation link module 140 can provide the third party with access to the request for data through the third party's tenant instance. In addition, if the request for data involves an artifact such as an electronic assessment, the process invitation link module 140 can provide the third party with access to the electronic assessment through the third party's tenant instance.


In additional or alternative aspects, when the data exchange computing platform 100 receives a request from the third party to claim a third party trust profile, the data exchange computing platform 100 executes a claim profile module 145 to process the request. The claim profile module 145 locks the third party trust profile so that the trust profile is unavailable for another third party to claim. The claim profile module 145 receives an indication as to whether the request is valid. If the request is valid, then the claim profile module 145 links the third party trust profile to the third party's tenant instance. As a result, the data exchange computing platform 100 provides the third party with access to the third party trust profile through the third party's tenant instance and allows the third party to control the data (e.g., artifacts) that is made available to other tenants of the data exchange service through the third party trust profile. Further details on the different modules is provided.


Artifact Request Module


Turning now to FIG. 2, additional details are provided regarding an artifact request module 110 used for processing a request submitted by a first party for data from a third party in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 2 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the artifact request module 110.


The data exchange computing platform 100 can allow a first party (e.g., personnel thereof) to log into the data exchange service and upon logging in, provided the first party with a portal (e.g., one or more graphical user interfaces) that allows the first party to perform functionality through the party's tenant instance. One such functionality is submitting a request for a third party to provide data such as an artifact. The artifact can be, for example, a particular piece of data such as an assessment, document, certification, and/or the like. Accordingly, the data exchange computing platform 100 can invoke the artifact request module 110 to process the request.


The process 200 involves the artifact request module 110 receiving the request in Operation 210. The request may include information needed to process the request such as, for example, the name of the artifact, the type of artifact being requested, instructions for the request, an identifier (e.g., name) of the first party, an identifier (e.g., name) of the third party, a contact (e.g., email address) for the third party, and/or the like. In some aspects, the first party (personnel thereof) provides some or all of the information when submitting the request. In additional or alternative aspects, the data exchange computing platform 100 may retrieve some or all of the information from the repository 150. For example, the data exchange computing platform 100 may have sent the third party another request in the past and in doing so, store information on the third party in the repository 150, or the third party may currently be a tenant of the data exchange service and therefore, information on the third party may be stored in the repository 150 accordingly.


The artifact request module 110 logs the request in Operation 215. In some aspects, the artifact request module 110 logs the request by recording the request in the repository 150. In addition, the artifact request module 110 may record an initial status of the request as “open.”


In Operation 220, the artifact request module 110 determines whether the third party is currently a tenant of the data exchange service. In some aspects, the information provided along with the request may indicate that the third party is or is not a current tenant of the data exchange service. In alternative aspects, the artifact request module 110 may query the data exchange computing platform 100 (e.g., the repository 150) to determine whether a tenant instance currently exists on the data exchange computing platform 100 for the third party.


In various aspects, the data exchange computing platform 100 allows for first parties to identify (e.g., “link” with) those third parties who are also tenants of the data exchange service that the first parties would like to exchange data with through the data exchange service. Here, the data exchange computing platform 100 may provide a first party (e.g., personnel thereof) with functionality through the first party's tenant instance (e.g., via the first party's portal) to allow personnel for the first party to identify those third parties that the first party would like to exchange data with through the data exchange service. For example, the data exchange computing platform 100 can provide the personnel with one or more graphical user interfaces that lists the third parties who are current tenants of the data exchange service. Therefore, the personnel can select which third parties that the first party would like to exchange data with through the data exchange service.


In some aspects, the data exchange computing platform 100 may first solicit approval from the third party before linking the third party with the first party. For example, the data exchange computing platform 100 may send a notification to the third party requesting the third party approve the first party's request to be linked with the third party so that the two parties can exchange data through the data exchange service. Once approved, the data exchange computing platform 100 can then link the first party and third party in the data exchange service (e.g., link the first party's tenant instance with the third party's tenant instance on the data exchange computing platform 100). Therefore, in these instances, the artifact request module 110 can determine whether to treat the third party as a current tenant of the data exchange service, with respect to the first party, by determining whether the third party is linked with the first party in the data exchange service.


If the third party is currently a tenant of the data exchange service, then the artifact request module 110 creates the request in the third party's tenant instance in Operation 225. As a result, the request becomes available to access through the third party's tenant instance. In some aspects, the data exchange computing platform 100 may provide an upload mechanism in the third party's tenant instance to allow the third party to upload the artifact being requested. For example, the artifact request module 110 may provide a control such as a button that allows the third party (personnel thereof) to navigate and choose an electronic document (e.g., file) from a third party tenant computing system 181 to upload into the data exchange computing platform 100. In this regard, the data exchange computing platform 100 provides the third party (the third party's computing environment 180) with a single, secure interface through which the third party can provide artifacts to a variety of first parties (first parties' computing environments 170).


In addition to providing access to the request, the artifact request module 110 creates an electronic notification to send to the third party in Operation 230. For example, depending on the contact available for the third party, the electronic notification can be in the form of an electronic communication such as an email, text message, platform message (e.g., LinkedIn®), and/or the like. In some aspects, the artifact request module 110 creates the electronic notification to include an access mechanism that the third party (e.g., personnel thereof) can use to access the request. For example, the access mechanism may comprise a request link such as a hyperlink that the personnel can select to access the third party's tenant instance.


The artifact request module 110 sends the electronic notification on behalf of the first party to notify the third party of the request made by the first party in Operation 245. Upon activating the link, the data exchange computing platform 100 may facilitate the third party (e.g., personnel thereof) logging into the data exchange service and provide the personnel with a tenant portal to access the third party's tenant instance. For example, the tenant portal may comprise one or more graphical user interfaces such as one or more webpages that are displayed through a browser application residing on a computing device of a third party tenant computing system 181.


If the third party is not currently a tenant of the data exchange service, then the artifact request module 110 verifies the contact provided along with the request in Operation 235. In various aspects, the artifact request module 110 performs this particular operation by verifying the personnel (e.g., individual) who is associated with the contact is also associated with the third party. In some aspects, the artifact request module 110 verifies the contact through soliciting (e.g., query) one or more publicly available data sources. For example, the artifact request module 110 may verify the individual is associated (e.g., employed) with the third party through soliciting a professional networking platform such as LinkedIn®, Xing, MeetUp®, Bark, and/or the like.


In additional or alternative aspects, the artifact request module 110 assigns a respondent to the request to verify the contact. A respondent may be personnel who is responsible for ensuring the contact is associated with the third party. For example, the respondent may verify that the contact is associated with the third party by searching one or more publicly available data sources, directly contacting the contact, contacting the third party, and/or the like. Once verified, the artifact request module 110 may receive an indication that the contact has been verified for the request.


In some aspects, the artifact request module 110 creates an electronic notification to send to the third party in Operation 240. Again, depending on the contact available for the third party, the electronic notification can be in the form of an electronic communication such as an email, text message, platform message (e.g., LinkedIn®), and/or the like. Here, the artifact request module 110 can create the electronic notification to include an invitation mechanism that the third party (e.g., personnel thereof) can use to register with the data exchange service, and subsequently access the request. For example, similar to the access mechanism, the invitation mechanism may comprise an invitation link such as a hyperlink that the personnel can select to access a guest portal for the data exchange service that can be used to register the third party with the data exchange service.


Therefore, in Operation 245, the artifact request module 110 sends the electronic notification on behalf of the first party to notify the third party of the request made by the first party and to invite the third party to register with the data exchange service. Upon activating the link, the data exchange computing platform 100 may provide personnel for the third party with a guest portal that can be used in registering with the data exchange service. For example, the guest portal may comprise one or more graphical user interfaces such as one or more webpages that are displayed through a browser application residing on a computing device of a third party tenant computing system 181.


It is noted that in some aspects, depending on the circumstances and/or responsibilities of the respondent, the artifact request module 110 may or may not send the electronic notification with the invitation link to the third party, or may not send the electronic notification upon receiving the request. Instead, the respondent, independent of the artifact request module 110, may verify the contact for the third party and then send the electronic notification to the third party accordingly.


Process Request Link Module


Turning now to FIG. 3, additional details are provided regarding a process request link module 115 used for fulfilling an artifact request in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 3 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the process request link module 115.


The data exchange computing platform 100 may receive a request for an artifact to be sent to a third party submitted by a first party through the data exchange service. In turn, the data exchange computing platform 100 (e.g., the artifact request module 110) may generate and send an electronic notification on behalf of the first party that includes an access mechanism that personnel for the third party may activate to gain access to the request. Upon activation, the data exchange computing platform 100 may provide the personnel with a login portal to facilitate the personnel logging into the data exchange service. For example, the login portal may comprise one or more graphical user interfaces such as one or more webpages that are displayed through a browser application residing on a computing device of a third party tenant computing system 181.


Upon successful login, the data exchange computing platform 100 activates the process request link module 115 and provides the module 115 with the login (e.g., information on the third party who has successfully logged into the data exchange service). Therefore, the process 300 involves the process request link module 115 receiving the login at Operation 310. In turn, the process request link module 115 provides the personnel for the third party with a tenant portal in Operation 315. Again, the tenant portal may comprise one or more graphical user interfaces such as one or more webpages that are displayed through the browser application.


In general, the tenant portal provides the personnel with access to the third party's tenant instance. In doing so, the tenant portal may provide the personnel with access to certain functionality that can be performed through the data exchange service. For example, the tenant portal may provide the personnel with access to functionality that allows the personnel to view a request for an artifact that has been submitted by a first party for the third party. In addition, the tenant portal may provide the personnel with access to functionality that allows the personnel to upload an artifact into the data exchange computing platform 100 so that the artifact can be made available to one or more first parties. Further, the tenant portal may provide the personnel with access to functionality that allows the personal to download and/or access an electronic assessment that has been requested to be completed by a first party. Furthermore, the tenant portal may provide the personnel with access to functionality that assists the personnel in completing an electronic assessment that has been requested to be completed by a first party.


Therefore, in Operation 320, the process request link module 115 determines whether the current request being made of the third party involves the third party completing an electronic assessment for the first party. If so, then the process request link module 115 provides access to the electronic assessment through the third party's tenant instance in Operation 325. Accordingly, the electronic assessment (e.g., assessment file) may be provided in various formats such as, for example, an Excel® spreadsheet, a Word® document, a fillable portable document format (PDF) file, and/or the like. Thus, the process request link module 115 can provide access to the electronic assessment that enables the personnel to the download the assessment from the data exchange computing platform 100 to a third party tenant computing system 181 if desired.


Per the personnel's request, the process request link module 115 may upload an artifact into the data exchange computing platform 100 in Operation 330. For example, per the personnel's request, the process request link module 115 may upload an artifact (e.g., a completed version of an assessment) into the data exchange computing platform 100 to fulfill the request for the artifact submitted by the first party. Here, the data exchange computing platform 100 can provide the personnel with an upload mechanism available through the tenant portal to facilitate uploading the artifact into the data exchange computing platform 100. For example, the tenant portal may provide a control such as a button that allows the third party personnel to navigate and choose the artifact (e.g., an electronic file) from a third party tenant computing system 181 to upload into the data exchange computing platform 100.


Once uploaded, the process request link module 115 may determine whether to save the uploaded artifact in Operation 335. For example, the process request link module 115 may cause the tenant portal to inquire as to whether the third party would like to have the uploaded artifact saved on the data exchange computing platform 100 so that the artifact may be used for fulfilling future requests made by first parties. If the process request link module 115 receives a positive response from the personnel, then the process request link module 115 saves the artifact in the repository 150 of the data exchange computing platform 100 in Operation 340. In various aspects, the data exchange computing platform 100 may then make the artifact available to the third party through the third party's tenant instance. As a result, the data exchange computing platform 100, upon request, can then provide the artifact to other first parties who are tenants through the data exchange service without having to upload the artifact again into the data exchange computing platform 100.


In Operation 345, the process request link module 115 determines whether to share the uploaded artifact with the first party who submitted the request for the artifact. Again, the process request link module 115 may cause the tenant portal to inquire as to whether the third party would like to share the uploaded artifact with the first party who submitted the request for the artifact. If the process request link module 115 receives a positive response from the personnel, then the process request link module 115 sends an electronic notification to the first party indicating the artifact is now available through the data exchange service in Operation 350. In addition, the process request link module 115 sets the request status to “completed” in Operation 355.


Accordingly, the process request link module 115 may provide the first party with access to the artifact through the first party's tenant instance on the data exchange computing platform 100. In doing so, the data exchange computing platform 100 can facilitate exchange of the artifact between the first and third parties without the first party's computing environment 170 and the third party's computing environment 180 having to directly interact to exchange the artifact. As a result, the data exchange computing platform 100 can address any technical challenges that may be encountered due to different functionality, capabilities, interfaces, and/or the like between the first party and third party computing environments 170, 180.


Autocompletion Assessment Module


Turning now to FIG. 4, additional details are provided regarding an autocompletion assessment module 120 used for autocompleting an electronic assessment in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 4 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the autocompletion assessment module 120.


In various aspects, the data exchange computing platform 100 provides functionality through the data exchange service that can assist a third party (e.g., personnel thereof) in completing an electronic assessment. The electronic assessment can involve a set of questions that a first party has asked the third party to provide answers to in the assessment. In various aspects, the functionality provided through the data exchange computing platform 100 can automatically identify answers to one or more questions in the set of questions. The data exchange computing platform 100 can make such functionality available to third parties through the third parties' tenant instances. Therefore, upon receiving an indication that a third party has access the functionality through the third party's tenant instance, the data exchange computing platform 100 can invoke the autocompletion assessment module 120.


The process 400 involves the autocompletion assessment module 120 ingesting the electronic assessment (assessment file) in Operation 410. This operation may involve extracting the set of questions from the assessment file. For example, the assessment file may be in various formats such as an Excel® spreadsheet, a Word® document, a fillable portable document format (PDF) file, and/or the like. In various aspects, the autocompletion assessment module 120 performs this particular operation by invoking an ingest module 125. In turn, the ingest module 125 extracts the set of questions from the assessment file. In addition to extracting the set of questions, the ingest module 125 can generate a mapping of the set of questions and/or one or more positions for each question in the set of questions where one or more answers to the question are to be provided in the assessment file.


In Operation 415, the autocompletion assessment module 120 generates answers for one or more questions in the set of questions found in the assessment file. In various aspects, the autocompletion assessment module 120 performs this particular operation by invoking an identify answers module 130. The identify answers module 130 generates the answers for one or more questions in the set of questions by identifying previous answers provided by the third party to previous questions found in one or more previous assessments completed by the third party that are similar to the questions found in the set of questions. Here, the data exchange computing platform 100 may generate and store one or more answer libraries for the third party that include the previous questions and answers that can be used by the identify answers module 130 in generating the answers for the one or more questions in the set of questions found in the assessment file.


In Operation 420, the autocompletion assessment module 120 displays the generated answers for the one or more questions in the set of questions to the personnel for the third party. Here, the autocompletion assessment module 120 may provide one or more graphical user interfaces for display through the third party's tenant portal. The graphical user interface(s) may display the answers generated for the one or questions so that the personnel for the third party can review the accuracy of the answers. In some aspects, the graphical user interface(s) also display a confidence measure (e.g., score) for the one or more answers identified for each question that indicates a level of confidence that the correct answers has been generated for the corresponding question. The confidence measure can allow for the personnel to quickly identify those answers that may need to be reviewed more closely to ensure that the answers are correct for the corresponding questions. The graphical user interface(s) may allow for the personnel to filter the answers based on the confidence measures to further assist the personnel in identify those answers that may need to be reviewed more closely.


In addition, the one or more graphical user interfaces may provide the personnel with the capability to edit and revise the answers, as well as identify those answers that are incorrect for their corresponding questions. As a result, the autocompletion assessment module 120 can receive feedback input in Operation 425. The autocompletion assessment module 120 can then revise the answer libraries based on the feedback input in Operation 430.


In some aspects, the autocompletion assessment module 120 can perform this operation by updating the one or more corresponding previous answers for a particular previous question found in an answer library to reflect the one or more answers that were revised by the personnel. In additional or alternative aspects, the autocompletion assessment module 120 can perform this operation by revising an answer library to include a question, and one or more corresponding answers, in which an incorrect answer was identified for the question. In this way, the autocompletion assessment module 120 can update the answer library to include the question as an additional previous question, along with the one or more corresponding answers as previous answer(s), so that the autocompletion assessment module 120 can then identify the correct answer(s) for the question in the future. In addition, the autocompletion assessment module 120 can generating a token representation of the question to also include in the answer library.


In Operation 435, the autocompletion assessment module 120 populates the assessment file with the identifies answers to generate a completed version of the electronic assessment. Here, the autocompletion assessment module 120 can perform this operation by using the mapping of the set of questions and/or positions for each question in the set of questions to populate the answers in the assessment file. Once populated, the autocompletion assessment module 120 makes the assessment file available to the third party through the third party's tenant instance.


Ingest Module


Turning now to FIG. 5, additional details are provided regarding an ingest module 125 used for ingesting an electronic assessment into the data exchange computing platform 100 in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 5 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the ingest module 125.


The process 500 involves the ingest module 125 receiving locations of where the questions can be found and the answers are to be provided in the electronic assessment (e.g., the assessment file) in Operation 510. In various aspects, the ingest module (or some other module such as the autocompletion assessment module 120) can provide personnel of the third party with one or more graphical user interfaces through the third party's tenant portal that allow the personnel to enter locations of where the set of questions can be found in the assessment file, as well as where the corresponding answers are to be provided in the assessment file.


For example, the assessment file may be provided in a spreadsheet format such as an Excel® spreadsheet. Here, the ingest module 125 can receive a first input provided through the one or more graphical user interfaces of a first location where the set of questions is found in the assessment file such as, for example, a first column of the spreadsheet in which the set of questions are listed. In addition, the ingest module 125 can receive a second input through the one or more graphical user interfaces of a second location of where answers are to be provided for the set of questions such as, for example, a second column of the spreadsheet in which the answers to the set of questions are to be provided.


In some aspects, the ingest module 125 may receive additional information on the sets of questions and corresponding answers in addition to the first and second locations. For example, the ingest module 125 may receive a third input provided through the one or more graphical user interfaces of where question numbers for the set of questions can be found such as, for example, a third column of the spreadsheet in which the question numbers (e.g., 1, 2, 3, 4, etc.) are listed. In addition, the ingest module 125 may receive a fourth input through the one or more graphical user interfaces of a fourth location of where supporting answers are to be provided for the set of questions such as, for example, a fourth column of the spreadsheet in which the supporting answers to the set of questions are to be provided. For example, the spreadsheet may be designed to provide a yes/no response for each question in the set of questions in the second column of the spreadsheet and a more detailed response in support of the yes/no response for each question in the set of questions in the fourth column.


In Operation 515, the ingest module 125 can also receive subsections of the set of questions through the one or more graphical user interfaces. For example, the set of questions provided in the assessment file may be divided into subsections based on the type of question being asked. For example, a first subset of the set of questions may be directed to access controls that have been put into place by the third party with respect to a computer-implemented service being offered by the third party. As a specific example, the first subset of questions may include a first question as to whether the third party has implemented two-factor authentication for the service, a second question as to whether the third party has implemented physical access restrictions on the area in which a repository used to support the service is located, and so forth. A second subset of the set of questions may be directed to encryption controls that have been put into place by the third party with respect to data stored in the repository for the service. As a specific example, the second subset of questions may include a first question as to whether the third party encrypts the data before storing the data in the repository, a second question as to whether the third party makes any transfers of the data within its computing environment 180 without first encrypting the data, and so forth.


The ingest module 125 can receive input through the one or more graphical user interfaces that identifies these two subsections that contain the first subset of questions and the second subset of questions. In addition, the ingest module 125 can receive input through the one or more graphical user interfaces that provides a label for each subsection. Accordingly, the data exchange computing platform 100 may provide functionality via one or more graphical user interfaces to allow personnel to filter out each of the subset of questions found in each of the subsections for reviewing purposes.


For example, particular personnel of the third party may be responsible for ensuring the correct information is provided for the first subset of questions involving the access controls that have been put into place for the service. Therefore, the data exchange computing platform 100 (e.g., the autocompletion assessment module 120) can filter out the first subset of questions from the set of questions provided in the assessment file using the identified subsections to display to the particular personnel so that the personnel can more quickly and efficiently review the answers that have been identified for the first subset of questions.


In Operation 520, the ingest module 125 receives input of the one or more answer libraries that are applicable to the set of questions through the one or more graphical user interfaces. As previously noted, the data exchange computing platform 100 can generate and store one or more answer libraries for the third party. Therefore, the ingest module 125 can receive input on which of the one or more answer libraries stored on the data exchange computing platform 100 are applicable to the set of questions found in the assessment file.


In Operation 525, the ingest module 125 generates a mapping of the set of questions and corresponding answers found in the assessment file. In various aspects, the ingest module 125 performs this particular operation by identifying one or more positions in the assessment file for providing each answer (or answers) for each question in the set of questions based on the first location and the second location. In addition, the ingest module 125 may use other information such as the third location in which the question numbers are provided and/or a fourth location in which the supporting answers are provided in identifying the one or more positions in the assessment file for providing each answer (or answers) for each question in the set of questions.


For example, the ingest module 125 can identify, based on the first, second, third, and fourth locations, a first position as a first particular cell in the assessment file that is in the format of an Excel® spreadsheet to provide the yes/no answer for a first question found in the set of questions and a second position as a second particular cell in the assessment file to provide the supporting answer for the first question In addition, the ingest module 125 can identify a third position as a third particular cell in the assessment file to provide the yes/no answer for a second question found in the set of questions and a fourth position as a fourth particular cell in the assessment file to provide the supporting answer for the second question, and so forth. The ingest module 125 can then generate the mapping for the set of questions and corresponding answers based on the identified cells for each of the questions found in the set of questions.


In Operation 530, the ingest module 125 extracts the set of questions (e.g., text thereof) from the assessment file. The ingest module 125 can also perform this particular operation based on one or more of the locations. For example, the ingest module 125 can extract the set of questions, and corresponding question numbers, based on the first and third locations that identify the columns in which the set of questions are listed, and the question numbers are listed.


Identify Answers Module


Turning now to FIG. 6, additional details are provided regarding an identify answers module 130 used for identifying answers to the set of questions found in an electronic assessment (assessment file) in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 6 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the identify answers module 130.


The process 600 involves the identify answers module 130 selecting a question from the set of questions in Operation 610. Once selected, the identify answers module 130 generates a token representation of the question in Operation 615. In various aspects, the identify answers module 130 performs this particular operation by performing natural language processing on the question to generate a vector representation of the question that serves as the token representation. For instance, the identify answers module 130 can use a tokenization technique on the question to generate the vector representation of the question such as, for example, a count vectorizer, a TF-IDF vectorizer, and/or the like.


In Operation 620, the identify answers module 130 compares the generated token representation for the selected question with the token representations provided for the previous questions found in the one or more corresponding answer libraries. In various aspects, the identify answers module 130 performs this particular operation by generating a similarity measure between the two token representations. For example, the identify answers module 130 may generate a cosine measure, an overlap measure, a Euclidean measure, a dot product measure, and/or the like between the two token representations.


In Operation 625, the identify answers module 130 can then select the corresponding one or more answers for the previous question that appears to have a level of the similarity (e.g., similarly measure) that demonstrates the question, and the previous question are closely similar. In various aspects, the identify answers module 130 performs this particular operation based on the similarity measures generated between the token representation for the question and the token representations for each of the previous questions.


In some aspects, the identify answers module 130 also generates a confidence measure (e.g., confidence value) that identifies a confidence that the identified one or more answers are correct for the question. For example, the identify answers module can generate the confidence measure based on the number of words that match between the question and the previous question as indicated via their corresponding token representations. In addition, the identify answers module 130 may also determine that the confidence measure for the one or more identified answers satisfies a certain threshold in order to maintain the one or more answers are provided as answers for the question.


In various aspects, an answer library can be constructed to include the previous questions grouped into entries. Here, an entry may represent a group of previous questions that are related. For example, an entry may represent a group of previous questions related to requesting information on a third party's encryption practices. Accordingly, such a previous question may be asked via multiple variations. As a specific example, such a previous question may be asked as a yes/no question such as “do you use encryption for stored data?” In addition, such a previous question may be asked that solicits more detailed information such as “what type of encryption method do you use for stored data?” Therefore, an answer library may be constructed to include an entry to represent these two previous questions.


In some aspects, the entry may comprise a hierarchical structure that includes a primary previous question representing the entry, along with secondary previous questions that are treated as alternative questions for the entry. For example, the entry related to requesting information on a third party's encryption practices may identify the previous question “what type of encryption method do you use for stored data?” as the primary question for the entity, with the previous question “do you use encryption for stored data?” as a secondary question. In addition, an entry may include one or more previous answers associated with the entry. Accordingly, the one or more previous answers may be arranged in a hierarchical structure. For example, the one or more previous answers may be arranged so that a single previous answer is provided for each previous question found in the hierarchical structure for the entity.


Therefore, in some aspects, the identify answers module 130 can generate the confidence measure by initially identifying a previous question that matches the question based on the similarity measure generated between the previous question and the question. The identify answers module 130 can then generate the confidence measure based on the similarity measure and the similarity measures for the remaining previous questions found in the entry in which the identified previous question is found. In additional or alternative aspects, the identify answers module 130 can generate the confidence measure based on the number of words that match and the similarities measures for the previous questions found in the corresponding entry.


In additional or alternative aspects, the identify answers module 130 can perform one or more natural language processing techniques in confirming a closet match between the question and a previous question. For example, the identify answers module 130 can perform natural language processing techniques such as sentiment analysis, entity analysis, syntax analysis, and/or the like. Accordingly, the identify answers module 130 can perform such techniques to better improve the capabilities of the identify answers module 130 in accurately identifying the closets match to the question found in the previous questions.


In Operation 630, the identify answers module 130 determines whether another question is found in the set of questions for the assessment file. If so, then the identify answers module 130 returns to Operation 610, selects the next question in the set of questions, and determines one or more answers for the newly selected question as just discussed. Once the identify answers module 130 has processed all of the questions in the set of questions, the identify answers module 130 returns the answers in Operation 635. As discussed, the data exchange computing platform 100 (e.g., the autocompletion assessment module 120) can then display the identified answers for the set of questions to personnel of the third party to review through the third party's tenant portal.


Populate Assessment Module


Turning now to FIG. 7, additional details are provided regarding a populate assessment module 135 used for populating answers in an assessment (assessment file) in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 7 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the populate assessment module 135.


The process 700 involves the populate assessment module 135 selecting a question from the set of questions found in the assessment file that one or more answers have been identified for the question in Operation 710. The data exchange computing platform 100 (e.g., the autocompletion assessment module 120) may have first displayed the answers identified for the set of questions to personnel of the third party via one or more graphical user interfaces through the third party's tenant portal. In turn, the data exchange computing platform 100 (e.g., the autocompletion assessment module 120) may have received an indication for each question that the one or more answers identified for the question are correct. Therefore, the populate assessment module 135 may be provided with those questions (and/or indication thereof) in the set of questions in which answers have been identified as correct for the questions.


In Operation 715, the populate assessment module 135 identifies one or more positions in the assessment file to populate with the one or more answers identified for the question. In various aspects, the populate assessment module 135 performs this operation by using the mapping of the questions and answers generated for the assessment file (e.g., by the ingest module 125). For example, the populate assessment module 135 may use the question number and/or the question, itself, in identifying the one or more positions in the assessment file that are to be populated with the one or more answers for the question. As a specific example, the assessment file may be in the format of an Excel® spreadsheet. Here, the populate assessment module may identify a first particular cell in the spreadsheet for storing a first yes/no answer for the question and a second particular cell in the spreadsheet for storing a supporting answer for the question. Once the positions have been identified, the populate assessment module 135 populates the one or more positions (e.g., cells) in the assessment file with the one or mor answers for the question in Operation 720.


In Operation 725, the populate assessment module 135 determines whether another question exists in which one or more answers for the question need to be populated in the assessment file. If so, then the populate assessment module 135 returns to Operation 710, selects the next question, and populates the one or more answers for the newly selected question in the assessment file accordingly. Once the populate assessment module 135 has processed all of the questions that exist in which one or more answers for the questions are to be populated in the assessment file, the populate assessment module 135 provides the assessment file in Operation 730. For example, the populate assessment module 135 may provide the file to the autocompletion assessment module 120 and in turn, the autocompletion assessment module 120 may provide the third party (e.g., personnel thereof) with access to the assessment file through the third party's tenant portal.


Answer Library


As noted, the data exchange computing platform 100 can generate one or more answer libraries for a particular third party. In various aspects, the data exchange computing platform 100 can generate an answer library for a particular third party that comprises a set of previous questions and answers. For example, the data exchange computing platform 100 can receive one or more different electronic assessments (e.g., assessment files) that were previously completed by the third party and uploaded by personnel of the third party into the data exchange computing platform 100.


In turn, the data exchange computing platform 100 can extract the previous questions and corresponding answers found in each of the previously completed assessments to include in the answer library. In some aspects, the data exchange computing platform 100 can receive input from the personnel identifying locations within the previous assessment files that previous questions and corresponding previous answers can be found. Accordingly, the data exchange computing platform 100 can use the locations in extracting the previous questions and corresponding previous answers provided in the previous assessment files.


In additional or alternative aspects, the data exchange computing platform 100 can use a template in extracting the previous questions and corresponding previous answers from the previously completed assessments. For example, the data exchange computing platform 100 may receive a selection on a template from a listing of different templates that may be based on various types of layouts for assessments. Accordingly, the data exchange computing platform 100 can use the selected template in extracting the previous questions and corresponding answers from the assessments. The data exchange computing platform 100 can then use the extract previous questions and answers in generating the answer library for the third party.


However, many of the previous questions may be asking for the same and/or similarly related information. For example, a first previous question may ask “is your data repository located in a restricted area?” While a second previous question may ask “can you please provide details on what personnel have access to your data repository?” In addition, similar previous questions may be asking for the same information using different variations. For example, a first previous question may ask “does your computing service require two-factor authentication?” While a second previous question may ask “do you have two-factor authentication controls in place?” Therefore, the data exchange computing platform 100 can address these concerns in generating the answer library for the third party by clustering previous questions that are similar into groups of similar previous questions and identifying one or more previous answers for each of the groups of previous similar questions to include in the answer library.


In various aspects, the data exchange computing platform 100 clusters the previous questions by using a tokenization technique on each previous question to generate a token representation of the previous question. In some aspects, the data exchange computing platform 100 uses a count vectorizer that generates a token representation in the form of a vector out of each previous question based on a word count for each question. Here, a word listing can be generated that includes each unique word that appears in the previous questions extracted from the assessments. The data exchange computing platform 100 can then generate a vector for each previous question that includes a position for each word found in the word listing with the positions in the vector representing the words found in the previous question set to an integer to indicate an occurrence of the word in the question. For example, for the previous question “do you have two-factor authentication controls in place?,” the data exchange computing platform 100 can set the position in the vector representing the word “authentication” to a one, while setting all the positions in the vector representing the words found in the word listing that do not appear in the question to zero.


In additional or alternative aspects, the data exchange computing platform 100 can use other tokenization techniques such as a TF-IDF vectorizer that performs a similar process as the count vectorizer except the TF-IDF vectorizer replaces the integers in the positions representing the words that appear in a previous question with a calculated TF-IDF value. TF is the term frequency determined as the number of times the word appears in the previous question and IDF is the inverse document frequency determined as the log to the base e of the total number of previous questions divided by the number of previous questions in which the word appears.


In various aspects, the data exchange computing platform 100 then uses a clustering model to cluster the previous questions that are similar into groups of similar previous questions. The clustering model is configured to process the token representations to cluster the previous questions with high similarity based on the token representations generated for the various previous questions. For example, the clustering model may be configured to perform a k-nearest neighbor (k-NN) classification to place each previous question into a class membership to form the groups of similar previous questions.


Once all of the previous questions have been placed into a group, the data exchange computing platform 100 identifies one or more previous answers for each of the groups of similar previous questions to include in the answer library. In some aspects, the data exchange computing platform 100 can provide the third party (e.g., personnel thereof) with the different groups of similar previous questions along with the corresponding answers for the previous questions found in each group. For example, the data exchange computing platform 100 can display the different groups on one or more graphical user interfaces made available through the third party's tenant portal.


In various aspects, the data exchange computing platform 100 can place an entry in the library to represent one or more of the groups of similar previous questions. In some aspects, an entry comprises a hierarchical structure that includes a primary previous question representing the entry, along with secondary previous questions that are treated as alternative questions for the entry.


Here, the data exchange computing platform 100 can receive a selection of one or more groups of similar previous questions via the one or more graphical user interfaces that have been identify by personnel as related and that an entry should be included in the library for the one or more groups. In addition, the data exchange computing platform 100 can receive a selection of a particular previous question for the one or more groups of similar previous questions to serve as the primary previous question for the entry. Further, the data exchange computing platform 100 can receive a selection of which of the previous questions and corresponding previous answers from each of the one or more groups of similar previous questions. Accordingly, these identified previous questions can serve as secondary previous questions for the entry.


The data exchange computing platform 100 can then include the entries for the different groups of similar previous questions and corresponding answers, as identified via the one or more graphical user interfaces, in the answer library to generate the answer library. In addition to the selected previous questions and answers, the data exchange computing platform 100 can also include the token representation of each previous question in the answer library.


In various aspects, the data exchange computing platform 100 can generate multiple answer libraries for a particular third party. For example, the data exchange computing platform 100 can generate different answer libraries for a particular third party based on different types of assessments that are completed by the particular third party. In addition or alternatively, the data exchange computing platform 100 can generate different answer libraries for a particular third party based on different computer-implemented services and/or products offered by the particular third party. The data exchange computing platform 100 can use other criteria in generating multiple answer libraries for a particular third party.


Process Invitation Link Module


Turning now to FIGS. 8A and 8B, additional details are provided regarding a process invitation link module 140 used for registering a third party with the data exchange service in accordance with various aspects. Accordingly, the flow diagram shown in FIGS. 8A and 8B may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the process invitation link module 140.


A first party may submit a request for an artifact to be sent to a third party through the data exchange service. In turn, the data exchange computing platform 100 (e.g., the artifact request module 110) may determine the third party is not currently a tenant of the data exchange service. As a result, the data exchange computing platform 100 (e.g., the artifact request module 110) may generate and send an electronic notification on behalf of the third party that includes an invitation and/or access mechanism that personnel for the third party may activate to register the third party with the data exchange service and/or to gain access to the request. Upon activation, the data exchange computing platform 100 may provide the personnel with a guest portal that facilitates the personnel initiating a registration of the third party with the data exchange service to gain access to the request, or in the alternative to gain access to the request as a guest of the data exchange service. For example, the guest portal may comprise one or more graphical user interfaces such as one or more webpages that are displayed through a browser application residing on a computing device of a third party tenant computing system 181.


Upon the personnel making a selection, the data exchange computing platform 100 activates the process invitation link module 140 and provides the module 140 with the selection made by the personnel of registering the third party with the data exchange service to gain access to the quest or to gain access to the request as a guest. Therefore, the process 800 involves the process invitation link module 140 receiving the selection at Operation 810. In turn, the process invitation link module 140 determines whether the personnel would like to continue as a guest in Operation 815. If so, then the process invitation link module provides the personnel with access to the request submitted by the first party through the guest portal in Operation 820.


If the process invitation link module 140 determines that the personnel instead wants to register the third party with the data exchange service, then the process invitation link module receives validation data in Operation 825. In some aspects, the process invitation link module automatically receives the validation data. For example, the validation data can be automatically populated in the guest portal as a result of an activation of the invitation and/or access mechanism sent to the third party. As a specific example, the invitation and/or access mechanism may comprise a link, such a hyperlink, that includes the validation data such as a contact (e.g., email address), a validation code, and/or the like that is populated in the guest portal upon activation of the link.


Here, the validation data may be unique to the third party so that the validation data can only be used in registering the third party with the data exchange service. In addition, the guest portal may lock the validation data once the data has been populated in the guest portal so that the validation data cannot be edited by the personnel. The guest portal may be configured in such a manner as to ensure that the validation data has been populated in the guest portal via the invitation and/or access mechanism, and that the third party (personnel thereof) is actually registering the third party with the data exchange service.


In additional or alternative aspects, the process invitation link module 140 may provide one or more graphical user interfaces for display to the personnel. Here, the one or more graphical user interfaces may request the personnel to provide the validation data such as a contact (e.g., email address), a validation code, and/or the like through which the third party received the invitation (e.g., the invitation and/or access mechanism) to register with the data exchange service. For example, the process invitation link module 140 may provide a graphical user interface for display that requests the validation data and provides an input control on the interface for the personnel to fill in and submit the contact.


In Operation 830, the process invitation link module 140 validates the registration of the third party with the data exchange service based on the validation data. For example, the process invitation link module 140 may compare the validation data (e.g., the contact, the validation code, and/or the link) with validation data the data exchange computing platform 100 has linked to the invitation and/or access mechanism sent to the third party. In various aspects, the process invitation link module 140 performs the validation to ensure that proper (e.g., authorized) personnel who are actually associated with the third party are registering the third party with the data exchange service.


In additional or alternative aspects, the process invitation link module 140 may also perform one or more checks in validating the registration of the third party with the data exchange service. For example, the process invitation link module 140 may determine whether the contact (e.g., personnel associated with the contact) and/or third party has been placed on a blacklist that prohibits the contact in registering a third party with the data exchange service and/or the third party is prohibited with registering with the data exchange service. In another example, the process invitation link module 140 may determine whether the contact (e.g., personnel associated with the contact) is associated with a competitor of the third party.


In Operation 835, the process invitation link module 140 determines whether the registration of the third party has been validated. If not, then the process invitation link module 140 may provide the personnel with an error in Operation 840. For example, the process invitation link module 140 may cause the display of an error message via the guest portal to indicate to the personnel that an error has occurred in validating the registration of the third party with the data exchange service.


Turning to FIG. 8B, if instead the process invitation link module 140 determines that the registration of the third party has been validated, then the process invitation link module 140 sends a tenant notification to the third party in Operation 845. For example, the process invitation link module 140 may send the third party an electronic communication, such as an email, text message, platform message (e.g., LinkedIn®), and/or the like, to the third party to notify the third party that an attempt is being made to register the third party with the data exchange service. In addition, the tenant notification may include credentials for the third party to use to access the data exchange service (e.g., to access the third party's tenant instance) such as a username and/or password. Further, the tenant notification may include a confirmation mechanism, such as a hyperlink, that the third party (e.g., personnel thereof) can activate to confirm the third party's registration with the data exchange service.


In Operation 850, the process invitation link module 140 determines whether confirmation for registration of the third party with the data exchange service has been received. For example, the process invitation link module 140 may receive an indication of the third party (e.g., personnel thereof) logging into the data exchange service using the credentials sent to the third party. In an additional or alternative example, the process invitation link module 140 may receive an indication of an activation of the confirmation mechanism provided in the tenant notification sent to the third party. If confirmation is not received (e.g. within a particular time period and/or an indication is received that registration of the third party has not been confirmed), then the process invitation link module 140 simply exists the process 800 in Operation 855.


However, if the process invitation link module 140 determines the registration of the third party has been confirmed, then the process invitation link module 140 generates a tenant instance for the third party on the data exchange computing platform 100 in Operation 860. In addition to generating the tenant instance, the process invitation link module 140 can create a link to access the request submitted by the first party on the third party's tenant instance in Operation 865. In addition, the process invitation link module 140 can determine whether the request involves an electronic assessment that the first party has submitted to have the third party complete in Operation 870. If so, then the process invitation link module 140 can create a link to access the electronic assessment on the third party's tenant instance in Operation 875. The process invitation link module 140 can then exist the process 800 in Operation 860.


As a result, the data exchange computing platform 100 can make the request, and accompanying electronic assessment if there is one, available through the data exchange service. Therefore, upon the data exchange computing platform 100 receiving an indication of the third party (personnel thereof) logging into the service, the data exchange computing platform 100 can provide the third party with access to the request and/or the electronic assessment through the third party's tenant instance.


The data exchange computing platform 100 may then receive an artifact uploaded through the third party's tenant instance to fulfill the request and in turn, make the uploaded artifact available to the first party who submitted the request through the first party's tenant instance on the data exchange computing platform 100. In doing so, the data exchange computing platform 100 can facilitate exchange of the artifact between the first and third parties without the first party's computing environment 170 and the third party's computing environment 180 having to directly interact to exchange the artifact. As a result, the data exchange computing platform 100 can address many of the technical challenges that may be encountered due to different functionality, capabilities, interfaces, and/or the like between the first party and third party computing environments 170, 180.


Claim Profile Module


Turning now to FIG. 9, additional details are provided regarding a claim profile module 145 used for linking a trust profile to a third party tenant instance in accordance with various aspects. Accordingly, the flow diagram shown in FIG. 9 may correspond to operations executed, for example, by computing hardware found in the data exchange computing platform 100 as described herein, as the computing hardware executes the claim profile module 145.


In various aspects, the data exchange computing platform 100 provides third party trust profiles to further assist third parties with providing first parties with access to data (e.g., various artifacts) of the third parties. A third party trust profile can serve as an electronic forum available through the data exchange service that is controlled by a particular (associated) third party with respect to making data available through the third part trust profile.


In various aspects, the data exchange computing platform 100 may provide one or more graphical user interfaces through the data exchange service to allow third parties (e.g., personnel thereof) to view third party trust profiles that have been created on the data exchange computing platform 100 for various third parties, but have yet to be claimed by the third parties. For example, the data exchange computing platform 100 may include a third party trust profile that may have been created for a particular third party who is not currently a tenant of the data exchange service, but who provides a service that is frequently used by many of the first parties who are tenants of the data exchange service. Here, the third party trust profile for the particular third party may provide information that is publicly available for the third party that may have been gathered from publicly available data sources such as the particular third party's public facing website. The data exchange computing platform 100 may include such third party trust profiles to make the publicly available information more readily and/or conveniently available for first party tenants of the data exchange service.


Accordingly, the particular third party may become a tenant of the data exchange service and decide to claim the third party trust profile or may instead, as a guest of the data exchange service, decide to claim the third party trust profile. Therefore, the data exchange computing platform 100 may receive a request from the particular third party (e.g., third party claimant) to claim the third party trust profile that is available through the data exchange service, but has not yet been claimed by the third party. Upon receiving the request, the data exchange computing platform 100 can invoke the claim profile module 145 to process the request.


Therefore, the process 900 involves the claim profile module 145 receiving the request in Operation 910. In response to receiving the request, the claim profile module 145 locks the third party trust profile on the data exchange computing platform 100 in Operation 915 so that the trust profile is unavailable for another third party to claim. The claim profile module 145 performs this particular operation in various aspects so that a third party trust profile on the data exchange computing platform 100 is not (accidently) linked to multiple third parties.


In Operation 920, the claim profile module 145 determines whether the third party's request to claim the third party trust profile is valid. In some aspects, the claim profile module 145 performs this particular operation without human intervention, or with minimal human intervention. For example, the request may include data (information) on the third party and/or personnel (e.g., an individual) who is submitting the request that can then be used by the claim profile module 145 to validate the request for the third party trust profile. As a specific example, the data may include identification information on personnel (e.g., the individual) who submitted the request on behalf of the third party. Here, the claim profile module 145 may use the identification information to investigate publicly available information found through various data sources (e.g., information found on LinkedIn®) to determine that the request is legitimate and that the proper third party (and/or personnel thereof) is claiming the third party trust profile. In other aspects, the claim profile module 145 submits the request to validation personnel who then conducts a validation process to validate that the request is legitimate.


If the claim profile module 145 determines the request has not been validated, then the claim profile module 145 unlocks the third party trust profile in Operation 925. As a result, the third party trust profile is again available through the data exchange service to be claimed by another (e.g., valid) third party. In Operation 930, the claim profile module 145 informs the third party that the request to link the third party profile with the third party (with the third party's tenant instance) could not be validated and has been rejected. For example, the claim profile module 145 may provide an electronic notification through the third party's tenant instance and/or the claim profile module 145 may send an electronic notification, such as an email, to the third party informing the third party that the request has been rejected.


If instead the claim profile module 145 determines the request has been validated, then the claim profile module 145 determines whether the third party is a current tenant of the data exchange service in Operation 935. If the claim profile module 145 determines the third party is not currently a tenant of the data exchange service, then the claim profile module 145 creates a tenant instance for the third party on the data exchange computing platform 100 in Operation 940. In various aspects, the claim profile module 145 may perform this particular operation in a similar manner as the process invitation link module 140. For example, the claim profile module 145 may perform validation and/or confirmation operations similar to the validation and/or confirmation operations performed by the process invitation link module 140.


In Operation 945, the claim profile module 145 links the third party trust profile to the third party's tenant instance. In Operation 930, the claim profile module 145 notifies the third party that the third party trust profile has been linked to the third party's tenant instance. For example, the claim profile module 145 may provide a notification through the third party's tenant instance and/or the claim profile module 145 may send an electronic notification, such as an email, to the third party informing the third party that the third party trust profile has been linked to the third party's tenant instance. As a result, the data exchange computing platform 100 provides access and control of the third party trust profile to the third party (e.g., personnel thereof) through the third party's tenant instance on the data exchange computing platform 100.


In various aspects, the data exchange computing platform 100 can provide a third party with the capabilities to claim and management multiple trust profiles that are associated with the third party. For example, a particular third party may wish to maintain separate trust profiles for each of the third party computer-implemented services being offered by the third party. The data exchange computing platform 100 providing the particular third party with the multiple trust profiles can allow for first parties to location and access needed data (e.g., needed artifacts) for a particular computer-implemented service that is being offered by the particular third party without the first parties having to sift through data for other computing-implemented services being offered by the particular third party. That is to say, the data exchange computing platform 100 providing the particular third party with the multiple trust profiled can facilitate more efficient and effective exchange of data between the particular third party and first parties.


In addition, the data exchange computing platform 100 can provide additional functionality for the trust profiles that can assist third parties in managing the trust profiles. For example, the data exchange computing platform 100 can provide functionality that allows for attachments to be made available along with certain data, auditing functionality that tracks and logs what first parties and/or personnel thereof who have access certain data through the trust profile, and/or the like.


Example Technical Platforms


Aspects of the present disclosure may be implemented in various ways, including as computer program products that comprise articles of manufacture. Such computer program products may include one or more software components including, for example, software objects, methods, data structures, and/or the like. A software component may be coded in any of a variety of programming languages. An illustrative programming language may be a lower-level programming language such as an assembly language associated with a particular hardware architecture and/or operating system platform. A software component comprising assembly language instructions may require conversion into executable machine code by an assembler prior to execution by the hardware architecture and/or platform. Another example programming language may be a higher-level programming language that may be portable across multiple architectures. A software component comprising higher-level programming language instructions may require conversion to an intermediate representation by an interpreter or a compiler prior to execution.


Other examples of programming languages include, but are not limited to, a macro language, a shell or command language, a job control language, a script language, a database query, or search language, and/or a report writing language. In one or more example aspects, a software component comprising instructions in one of the foregoing examples of programming languages may be executed directly by an operating system or other software component without having to be first transformed into another form. A software component may be stored as a file or other data storage construct. Software components of a similar type or functionally related may be stored together such as, for example, in a particular directory, folder, or library. Software components may be static (e.g., pre-established, or fixed) or dynamic (e.g., created or modified at the time of execution).


A computer program product may include a non-transitory computer-readable storage medium storing applications, programs, program modules, scripts, source code, program code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like (also referred to herein as executable instructions, instructions for execution, computer program products, program code, and/or similar terms used herein interchangeably). Such non-transitory computer-readable storage media include all computer-readable media (including volatile and non-volatile media).


In some aspects, a non-volatile computer-readable storage medium may include a floppy disk, flexible disk, hard disk, solid-state storage (SSS) (e.g., a solid-state drive (SSD), solid state card (SSC), solid state module (SSM)), enterprise flash drive, magnetic tape, or any other non-transitory magnetic medium, and/or the like. A non-volatile computer-readable storage medium may also include a punch card, paper tape, optical mark sheet (or any other physical medium with patterns of holes or other optically recognizable indicia), compact disc read only memory (CD-ROM), compact disc-rewritable (CD-RW), digital versatile disc (DVD), Blu-ray disc (BD), any other non-transitory optical medium, and/or the like. Such a non-volatile computer-readable storage medium may also include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory (e.g., Serial, NAND, NOR, and/or the like), multimedia memory cards (MMC), secure digital (SD) memory cards, SmartMedia cards, CompactFlash (CF) cards, Memory Sticks, and/or the like. Further, a non-volatile computer-readable storage medium may also include conductive-bridging random access memory (CBRAM), phase-change random access memory (PRAM), ferroelectric random-access memory (FeRAM), non-volatile random-access memory (NVRAM), magnetoresistive random-access memory (MRAM), resistive random-access memory (RRAM), Silicon-Oxide-Nitride-Oxide-Silicon memory (SONOS), floating junction gate random access memory (FJG RAM), Millipede memory, racetrack memory, and/or the like.


In some aspects, a volatile computer-readable storage medium may include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), fast page mode dynamic random access memory (FPM DRAM), extended data-out dynamic random access memory (EDO DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), double data rate type two synchronous dynamic random access memory (DDR2 SDRAM), double data rate type three synchronous dynamic random access memory (DDR3 SDRAM), Rambus dynamic random access memory (RDRAM), Twin Transistor RAM (TTRAM), Thyristor RAM (T-RAM), Zero-capacitor (Z-RAM), Rambus in-line memory module (RIMM), dual in-line memory module (DIMM), single in-line memory module (SIMM), video random access memory (VRAM), cache memory (including various levels), flash memory, register memory, and/or the like. It will be appreciated that where various aspects are described to use a computer-readable storage medium, other types of computer-readable storage media may be substituted for or used in addition to the computer-readable storage media described above.


Various aspects of the present disclosure may also be implemented as methods, apparatuses, systems, computing devices, computing entities, and/or the like. As such, various aspects of the present disclosure may take the form of a data structure, apparatus, system, computing device, computing entity, and/or the like executing instructions stored on a computer-readable storage medium to perform certain steps or operations. Thus, various aspects of the present disclosure also may take the form of entirely hardware, entirely computer program product, and/or a combination of computer program product and hardware performing certain steps or operations.


Various aspects of the present disclosure are described below with reference to block diagrams and flowchart illustrations. Thus, each block of the block diagrams and flowchart illustrations may be implemented in the form of a computer program product, an entirely hardware aspect, a combination of hardware and computer program products, and/or apparatuses, systems, computing devices, computing entities, and/or the like carrying out instructions, operations, steps, and similar words used interchangeably (e.g., the executable instructions, instructions for execution, program code, and/or the like) on a computer-readable storage medium for execution. For example, retrieval, loading, and execution of code may be performed sequentially such that one instruction is retrieved, loaded, and executed at a time. In some examples of aspects, retrieval, loading, and/or execution may be performed in parallel such that multiple instructions are retrieved, loaded, and/or executed together. Thus, such aspects can produce specially configured machines performing the steps or operations specified in the block diagrams and flowchart illustrations. Accordingly, the block diagrams and flowchart illustrations support various combinations of aspects for performing the specified instructions, operations, or steps.


Example System Architecture



FIG. 10 is a block diagram of a system architecture 1000 that can be used in providing the data exchange service that is accessible to various first and third party computing environments 170, 180 according to various aspects as detailed herein. As may be understood from FIG. 10, the system architecture 1000 in various aspects includes a data exchange computing platform 100. Here, the data exchange computing platform 100 can comprise one or more data exchange computing systems 1010. Each data exchange computing system 1010 can include various hardware components such as one or more data exchange servers 1015.


In addition, the data exchange computing platform 100 can include a repository 150. The repository 150 may be made up of one or more computing components such as servers, routers, data storage, networks, and/or the like that are used on the data exchange computing platform 100 to store and manage data associated with first and/or third parties who are tenants of the data exchange service. For example, the repository 150 may store and manage data associated with various tenant instances found on the data exchange computing platform 100 for the various first and/or third parties such as artifacts that are to be made available through the data exchange service, requests made for data artifacts through the data exchange service, third party trust profiles for various third parties, answer libraries used in autocompleting electronic assessments for various third parties, and/or the like.


Accordingly, the data exchange computing platform 100 may provide the data exchange service to various first and/or third parties by making the service available over one or more networks 160. Here, a first and/or third party may access the service via a first and/or third computing environment 170, 180 associated with the party interacting with the data exchange computing platform 100. For example, the data exchange computing platform 100 may provide the service through a website that is accessible to the first and/or third party's computing environment 170, 180 over the one or more networks 160.


According, the data exchange server(s) 1015 found within the one or more data exchange computing systems 1010 may execute an artifact request module 110, a process request link module 115, an autocompletion assessment module 120, an ingest module 125, an identify answers module 130, a populate assessment module 135, a process invitation link module 140, and/or a claim profile module 145 as described herein. Further, according to particular aspects, the data exchange server(s) 1010 may provide one or more portals that include one or more graphical user interfaces (e.g., one or more webpages, webform, and/or the like through the website) through which personnel of a first and/or third party can interact with the data exchange computing platform 100. Furthermore, the data exchange server(s) 1010 may provide one or more interfaces that allow the data exchange computing platform 100 to communicate with first and/or third party computing environment(s) 170, 180 such as one or more suitable application programming interfaces (APIs), direct connections, and/or the like.


Example Computing Hardware



FIG. 11 illustrates a diagrammatic representation of a computing hardware device 1100 that may be used in accordance with various aspects. For example, the hardware device 1100 may be computing hardware such as a data exchange server 1015 as described in FIG. 10. According to particular aspects, the hardware device 1100 may be connected (e.g., networked) to one or more other computing entities, storage devices, and/or the like via one or more networks such as, for example, a LAN, an intranet, an extranet, and/or the Internet. As noted above, the hardware device 1100 may operate in the capacity of a server and/or a client device in a client-server network environment, or as a peer computing device in a peer-to-peer (or distributed) network environment. In some aspects, the hardware device 1100 may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a mobile device (smartphone), a web appliance, a server, a network router, a switch or bridge, or any other device capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that device. Further, while only a single hardware device 1100 is illustrated, the term “hardware device,” “computing hardware,” and/or the like shall also be taken to include any collection of computing entities that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.


A hardware device 1100 includes a processor 1102, a main memory 1104 (e.g., read-only memory (ROM), flash memory, dynamic random-access memory (DRAM) such as synchronous DRAM (SDRAM), Rambus DRAM (RDRAM), and/or the like), a static memory 1106 (e.g., flash memory, static random-access memory (SRAM), and/or the like), and a data storage device 1118, that communicate with each other via a bus 1132.


The processor 1102 may represent one or more general-purpose processing devices such as a microprocessor, a central processing unit, and/or the like. According to some aspects, the processor 1102 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, a processor implementing other instruction sets, processors implementing a combination of instruction sets, and/or the like. According to some aspects, the processor 1102 may be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, and/or the like. The processor 1102 can execute processing logic 1126 for performing various operations and/or steps described herein.


The hardware device 1100 may further include a network interface device 1108, as well as a video display unit 1110 (e.g., a liquid crystal display (LCD), a cathode ray tube (CRT), and/or the like), an alphanumeric input device 1112 (e.g., a keyboard), a cursor control device 1114 (e.g., a mouse, a trackpad), and/or a signal generation device 1116 (e.g., a speaker). The hardware device 1100 may further include a data storage device 1118. The data storage device 1118 may include a non-transitory computer-readable storage medium 1130 (also known as a non-transitory computer-readable storage medium or a non-transitory computer-readable medium) on which is stored one or more modules 1122 (e.g., sets of software instructions) embodying any one or more of the methodologies or functions described herein. For instance, according to particular aspects, the modules 1122 include an artifact request module 110, a process request link module 115, an autocompletion assessment module 120, an ingest module 125, an identify answers module 130, a populate assessment module 135, a process invitation link module 140, and/or a claim profile module 145 as described herein. The one or more modules 1122 may also reside, completely or at least partially, within main memory 1104 and/or within the processor 1102 during execution thereof by the hardware device 1100—main memory 1104 and processor 1102 also constituting computer-accessible storage media. The one or more modules 1122 may further be transmitted or received over a network 160 via the network interface device 1108.


While the computer-readable storage medium 1130 is shown to be a single medium, the terms “computer-readable storage medium” and “machine-accessible storage medium” should be understood to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” should also be understood to include any medium that is capable of storing, encoding, and/or carrying a set of instructions for execution by the hardware device 1100 and that causes the hardware device 1100 to perform any one or more of the methodologies of the present disclosure. The term “computer-readable storage medium” should accordingly be understood to include, but not be limited to, solid-state memories, optical and magnetic media, and/or the like.


System Operation


The logical operations described herein may be implemented (1) as a sequence of computer implemented acts or one or more program modules running on a computing system and/or (2) as interconnected machine logic circuits or circuit modules within the computing system. The implementation is a matter of choice dependent on the performance and other requirements of the computing system. Accordingly, the logical operations described herein are referred to variously as states, operations, steps, structural devices, acts, or modules. These states, operations, steps, structural devices, acts, and modules may be implemented in software, in firmware, in special purpose digital logic, and any combination thereof. Greater or fewer operations may be performed than shown in the figures and described herein. These operations also may be performed in a different order than those described herein.


CONCLUSION

While this specification contains many specific aspect details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features that may be specific to particular aspects of particular inventions. Certain features that are described in this specification in the context of separate aspects also may be implemented in combination in a single aspect. Conversely, various features that are described in the context of a single aspect also may be implemented in multiple aspects separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination may in some cases be excised from the combination, and the claimed combination may be a sub-combination or variation of a sub-combination.


Similarly, while operations are described in a particular order, this should not be understood as requiring that such operations be performed in the particular order described or in sequential order, or that all described operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various components in the various aspects described above should not be understood as requiring such separation in all aspects, and the described program components (e.g., modules) and systems may be integrated together in a single software product or packaged into multiple software products.


Many modifications and other aspects of the disclosure will come to mind to one skilled in the art to which this disclosure pertains having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the disclosure is not to be limited to the specific aspects disclosed and that modifications and other aspects are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for the purposes of limitation.

Claims
  • 1. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by computing hardware, configure the computing hardware to perform operations comprising: receiving an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions;performing a tokenization technique on the set of questions to generate a first token representation of each question in the set of questions;identifying, based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein:the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, andthe first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on a similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question;generating, based on a level of the similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question, a first confidence measure, wherein the first confidence measure identifies a confidence in the first answer is correct for the first question;providing a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question and the first confidence measure;receiving, via the graphical user interface, an indication that the first answer is correct for the first question; andresponsive to receiving the indication, populating the electronic assessment with the first answer for the first question.
  • 2. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise: receiving a first input of a first location of the set of questions found in the electronic assessment;receiving a second input of a second location of answers to provide for the set of questions in the electronic assessment;identifying, based on the first location and the second location, a position in the electronic assessment for providing each answer for each question in the set of questions; andgenerating a mapping comprising the position in the electronic assessment for providing each answer for each question in the set of questions, wherein populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer.
  • 3. The non-transitory computer-readable medium of claim 2, wherein the operations further comprise extracting, based on the first location and the second location, each question in the set of questions from the electronic assessment.
  • 4. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise receiving a selection of the answer library from a set of answer libraries available for the entity.
  • 5. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise: receiving the at least one previous electronic assessment;extracting the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment;performing the tokenization technique on the set of previous questions to generate the second token representation of each previous question in the set of previous questions; andgenerating the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions.
  • 6. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise: identifying, based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer is correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; andresponsive to receiving the corrected answer, populating the electronic assessment with the corrected answer for the second question.
  • 7. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise: identifying, based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer is correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a second indication that the second answer is incorrect for the second question; andresponsive to receiving the second indication, updating the answer library to include the second question.
  • 8. A method comprising: receiving an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions;performing a tokenization technique on the set of questions to generate a first token representation of each question in the set of questions;identifying, based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein:the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, andthe first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on a similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question;generating, based on a level of the similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question, a first confidence measure, wherein the first confidence measure identifies a confidence in the first answer being correct for the first question;providing a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question and the first confidence measure;receiving, via the graphical user interface, an indication that the first answer is correct for the first question; andresponsive to receiving the indication, populating the electronic assessment with the first answer for the first question.
  • 9. The method of claim 8, further comprising: receiving a first input of a first location of the set of questions found in the electronic assessment;receiving a second input of a second location of answers to provide for the set of questions in the electronic assessment;identifying, based on the first location and the second location, a position in the electronic assessment for providing each answer for each question in the set of questions; andgenerating a mapping comprising the position in the electronic assessment for providing each answer for each question in the set of questions, wherein populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer.
  • 10. The method of claim 9, further comprising extracting, based on the first location and the second location, each question in the set of questions from the electronic assessment.
  • 11. The method of claim 8, further comprising receiving a selection of the answer library from a set of answer libraries available for the entity.
  • 12. The method of claim 8, further comprising: receiving the at least one previous electronic assessment;extracting the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment;performing the tokenization technique on the set of previous questions to generate the second token representation of each previous question in the set of previous questions; andgenerating the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions.
  • 13. The method of claim 8, further comprising: identifying, based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; andresponsive to receiving the corrected answer, populating the electronic assessment with the corrected answer for the second question.
  • 14. The method of claim 8, further comprising: identifying, based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a second indication that the second answer is incorrect for the second question; andresponsive to receiving the second indication, updating the answer library to include the second question.
  • 15. A system comprising: a non-transitory computer-readable medium storing instructions; anda processing device communicatively coupled to the non-transitory computer-readable medium,wherein, the processing device is configured to execute the instructions and thereby perform operations comprising:receiving an electronic assessment to be completed by an entity, wherein the electronic assessment comprises a set of questions;performing a tokenization technique on the set of questions to generate a first token representation of each question in the set of questions;identifying, based on an answer library generated for the entity, a first answer to a first question in the set of questions, wherein:the answer library comprises (i) a set of previous questions answered by the entity for at least one previous electronic assessment, (ii) a second token representation for each previous question in the set of previous questions, and (iii) a previous answer for each previous question in the set of previous questions, andthe first answer comprises the corresponding previous answer for a first previous question in the set of previous questions based on a similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question;generating, based on a level of the similarity between the corresponding second token representation for the first previous question and the corresponding first token representation for the first question, a first confidence measure, wherein the first confidence measure identifies a confidence in the first answer being correct for the first question;providing a graphical user interface for display, wherein the graphical user interface comprises the first answer to the first question and the first confidence measure;receiving, via the graphical user interface, an indication that the first answer is correct for the first question; andresponsive to receiving the indication, populating the electronic assessment with the first answer for the first question.
  • 16. The system of claim 15, wherein the operations further comprise: receiving a first input of a first location of the set of questions found in the electronic assessment;receiving a second input of a second location of answers to provide for the set of questions in the electronic assessment;identifying, based on the first location and the second location, a position in the electronic assessment for providing each answer for each question in the set of questions; andgenerating a mapping comprising the position in the electronic assessment for providing each answer for each question in the set of questions, wherein populating the electronic assessment with the first answer for the first question comprises referencing the mapping to identify the position in the electronic assessment for providing the first answer for the first question and populating the position with the first answer.
  • 17. The system of claim 16, wherein the operations further comprise extracting, based on the first location and the second location, each question in the set of questions from the electronic assessment.
  • 18. The system of claim 15, wherein the operations further comprise: receiving the at least one previous electronic assessment;extracting the set of previous questions and the previous answer for each previous question in the set of previous questions from the at least one previous electronic assessment;performing the tokenization technique on the set of previous questions to generate the second token representation of each previous question in the set of previous questions; andgenerating the answer library to include the set of previous questions, the second token representation for each previous question in the set of previous questions, and the previous answer for each previous question in the set of previous questions.
  • 19. The system of claim 15, wherein the operations further comprise: identifying, based on the answer library, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a corrected answer to the second question, wherein the corrected answer is based on a correction made to the second answer to the second question; andresponsive to receiving the corrected answer, populating the electronic assessment with the corrected answer for the second question.
  • 20. The system of claim 15, wherein the operations further comprise: identifying, based on the answer library generated for the entity, a second answer to a second question in the set of questions, wherein the second answer comprises a second corresponding previous answer for a second previous question in the set of previous questions based on a similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question;generating, based on a level of the similarity between the corresponding second token representation for the second previous question and the corresponding first token representation for the second question, a second confidence measure, wherein the second confidence measure identifies a second confidence in the second answer being correct for the second question;providing the second answer to the second question and the second confidence measure for display on the graphical user interface;receiving, via the graphical user interface, a second indication that the second answer is incorrect for the second question; andresponsive to receiving the second indication, updating the answer library to include the second question.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application Ser. No. 63/229,854, filed Aug. 5, 2021, which is hereby incorporated herein by reference in its entirety.

US Referenced Citations (1567)
Number Name Date Kind
4536866 Jerome et al. Aug 1985 A
4574350 Starr Mar 1986 A
5193162 Bordsen et al. Mar 1993 A
5276735 Boebert et al. Jan 1994 A
5329447 Leedom, Jr. Jul 1994 A
5404299 Tsurubayashi et al. Apr 1995 A
5535393 Reeve et al. Jul 1996 A
5560005 Hoover et al. Sep 1996 A
5668986 Nilsen et al. Sep 1997 A
5710917 Musa et al. Jan 1998 A
5761529 Raji Jun 1998 A
5764906 Edelstein et al. Jun 1998 A
5872973 Mitchell et al. Feb 1999 A
5913041 Ramanathan et al. Jun 1999 A
5913214 Madnick et al. Jun 1999 A
6016394 Walker Jan 2000 A
6122627 Carey et al. Sep 2000 A
6148297 Swor et al. Nov 2000 A
6148342 Ho Nov 2000 A
6240416 Immon et al. May 2001 B1
6240422 Atkins et al. May 2001 B1
6243816 Fang et al. Jun 2001 B1
6253203 Oflaherty et al. Jun 2001 B1
6263335 Paik et al. Jul 2001 B1
6272631 Thomlinson et al. Aug 2001 B1
6275824 Oflaherty et al. Aug 2001 B1
6282548 Burner et al. Aug 2001 B1
6330562 Boden et al. Dec 2001 B1
6363488 Ginter et al. Mar 2002 B1
6374237 Reese Apr 2002 B1
6374252 Althoff et al. Apr 2002 B1
6408336 Schneider et al. Jun 2002 B1
6427230 Goiffon et al. Jul 2002 B1
6442688 Moses et al. Aug 2002 B1
6446120 Dantressangle Sep 2002 B1
6463488 San Juan Oct 2002 B1
6484149 Jammes et al. Nov 2002 B1
6484180 Lyons et al. Nov 2002 B1
6516314 Birkler et al. Feb 2003 B1
6516337 Tripp et al. Feb 2003 B1
6519571 Guheen et al. Feb 2003 B1
6574631 Subramanian et al. Jun 2003 B1
6591272 Williams Jul 2003 B1
6601233 Underwood Jul 2003 B1
6606744 Mikurak Aug 2003 B1
6611812 Hurtado et al. Aug 2003 B2
6625602 Meredith et al. Sep 2003 B1
6629081 Cornelius et al. Sep 2003 B1
6633878 Underwood Oct 2003 B1
6662192 Rebane Dec 2003 B1
6662357 Bowman-Amuah Dec 2003 B1
6697824 Bowman-Amuah Feb 2004 B1
6699042 Smith et al. Mar 2004 B2
6701314 Conover et al. Mar 2004 B1
6721713 Guheen et al. Apr 2004 B1
6725200 Rost Apr 2004 B1
6732109 Lindberg et al. May 2004 B2
6754665 Futagami et al. Jun 2004 B1
6755344 Mollett et al. Jun 2004 B1
6757685 Raffaele et al. Jun 2004 B2
6757888 Knutson et al. Jun 2004 B1
6779095 Selkirk et al. Aug 2004 B2
6816944 Peng Nov 2004 B2
6826693 Yoshida et al. Nov 2004 B1
6850252 Hoffberg Feb 2005 B1
6886101 Glazer et al. Apr 2005 B2
6901346 Tracy et al. May 2005 B2
6904417 Clayton et al. Jun 2005 B2
6909897 Kikuchi Jun 2005 B2
6912676 Gusler et al. Jun 2005 B1
6925443 Baggett, Jr. et al. Aug 2005 B1
6938041 Brandow et al. Aug 2005 B1
6956845 Baker et al. Oct 2005 B2
6978270 Carty et al. Dec 2005 B1
6980927 Tracy et al. Dec 2005 B2
6980987 Kaminer Dec 2005 B2
6983221 Tracy et al. Jan 2006 B2
6985887 Sunstein et al. Jan 2006 B1
6990454 McIntosh Jan 2006 B2
6993448 Tracy et al. Jan 2006 B2
6993495 Smith, Jr. et al. Jan 2006 B2
6996807 Vardi et al. Feb 2006 B1
7003560 Mullen et al. Feb 2006 B1
7003662 Genty et al. Feb 2006 B2
7013290 Ananian Mar 2006 B2
7017105 Flanagin et al. Mar 2006 B2
7023979 Wu et al. Apr 2006 B1
7039594 Gersting May 2006 B1
7039654 Eder May 2006 B1
7047517 Brown et al. May 2006 B1
7051036 Rosnow et al. May 2006 B2
7051038 Yeh et al. May 2006 B1
7058970 Shaw Jun 2006 B2
7069427 Adler et al. Jun 2006 B2
7076558 Dunn Jul 2006 B1
7093200 Schreiber et al. Aug 2006 B2
7095854 Ginter et al. Aug 2006 B1
7100195 Underwood Aug 2006 B1
7120800 Ginter et al. Oct 2006 B2
7124101 Mikurak Oct 2006 B1
7124107 Pishevar et al. Oct 2006 B1
7127705 Christfort et al. Oct 2006 B2
7127741 Bandini et al. Oct 2006 B2
7133845 Ginter et al. Nov 2006 B1
7139999 Bowman-Amuah Nov 2006 B2
7143091 Charnock et al. Nov 2006 B2
7149698 Guheen et al. Dec 2006 B2
7165041 Guheen et al. Jan 2007 B1
7167842 Josephson, II et al. Jan 2007 B1
7167844 Leong et al. Jan 2007 B1
7171379 Menninger et al. Jan 2007 B2
7181438 Szabo Feb 2007 B1
7203929 Vinodkrishnan et al. Apr 2007 B1
7213233 Vinodkrishnan et al. May 2007 B1
7216340 Vinodkrishnan et al. May 2007 B1
7219066 Parks et al. May 2007 B2
7223234 Stupp et al. May 2007 B2
7225460 Barzilai et al. May 2007 B2
7234065 Breslin et al. Jun 2007 B2
7247625 Zhang et al. Jul 2007 B2
7251624 Lee et al. Jul 2007 B1
7260830 Sugimoto Aug 2007 B2
7266566 Kennaley et al. Sep 2007 B1
7272818 Ishimitsu et al. Sep 2007 B2
7275063 Horn Sep 2007 B2
7281020 Fine Oct 2007 B2
7284232 Bates et al. Oct 2007 B1
7284271 Lucovsky et al. Oct 2007 B2
7287280 Young Oct 2007 B2
7290275 Baudoin et al. Oct 2007 B2
7293119 Beale Nov 2007 B2
7299299 Hollenbeck et al. Nov 2007 B2
7302569 Betz et al. Nov 2007 B2
7313575 Carr et al. Dec 2007 B2
7313699 Koga Dec 2007 B2
7313825 Redlich et al. Dec 2007 B2
7315826 Guheen et al. Jan 2008 B1
7315849 Bakalash et al. Jan 2008 B2
7322047 Redlich et al. Jan 2008 B2
7330850 Seibel et al. Feb 2008 B1
7340447 Ghatare Mar 2008 B2
7340776 Zobel et al. Mar 2008 B2
7343434 Kapoor et al. Mar 2008 B2
7346518 Frank et al. Mar 2008 B1
7353204 Liu Apr 2008 B2
7353283 Henaff et al. Apr 2008 B2
7356559 Jacobs et al. Apr 2008 B1
7367014 Griffin Apr 2008 B2
7370025 Pandit May 2008 B1
7376835 Olkin et al. May 2008 B2
7380120 Garcia May 2008 B1
7382903 Ray Jun 2008 B2
7383570 Pinkas et al. Jun 2008 B2
7391854 Salonen et al. Jun 2008 B2
7398393 Mont et al. Jul 2008 B2
7401235 Mowers et al. Jul 2008 B2
7403942 Bayliss Jul 2008 B1
7409354 Putnam et al. Aug 2008 B2
7412402 Cooper Aug 2008 B2
7424680 Carpenter Sep 2008 B2
7428546 Nori et al. Sep 2008 B2
7428707 Quimby Sep 2008 B2
7430585 Sibert Sep 2008 B2
7454457 Lowery et al. Nov 2008 B1
7454508 Mathew et al. Nov 2008 B2
7478157 Bohrer et al. Jan 2009 B2
7480694 Blennerhassett et al. Jan 2009 B2
7480755 Herrell et al. Jan 2009 B2
7487170 Stevens Feb 2009 B2
7493282 Manly et al. Feb 2009 B2
7500607 Williams Mar 2009 B2
7512987 Williams Mar 2009 B2
7516882 Cucinotta Apr 2009 B2
7523053 Pudhukottai et al. Apr 2009 B2
7529836 Bolen May 2009 B1
7533113 Haddad May 2009 B1
7548968 Bura et al. Jun 2009 B1
7552480 Voss Jun 2009 B1
7562339 Racca et al. Jul 2009 B2
7565685 Ross et al. Jul 2009 B2
7567541 Karimi et al. Jul 2009 B2
7584505 Mondri et al. Sep 2009 B2
7584508 Kashchenko et al. Sep 2009 B1
7587749 Leser et al. Sep 2009 B2
7590705 Mathew et al. Sep 2009 B2
7590972 Axelrod et al. Sep 2009 B2
7603356 Schran et al. Oct 2009 B2
7606783 Carter Oct 2009 B1
7606790 Levy Oct 2009 B2
7607120 Sanyal et al. Oct 2009 B2
7613700 Lobo et al. Nov 2009 B1
7617136 Lessing et al. Nov 2009 B1
7617167 Griffis et al. Nov 2009 B2
7620644 Cote et al. Nov 2009 B2
7627666 Degiulio et al. Dec 2009 B1
7630874 Fables et al. Dec 2009 B2
7630998 Zhou et al. Dec 2009 B2
7636742 Olavarrieta et al. Dec 2009 B1
7640322 Wendkos et al. Dec 2009 B2
7650497 Thornton et al. Jan 2010 B2
7653592 Flaxman et al. Jan 2010 B1
7657476 Barney Feb 2010 B2
7657694 Mansell et al. Feb 2010 B2
7665073 Meijer et al. Feb 2010 B2
7665125 Heard et al. Feb 2010 B2
7668947 Hutchinson et al. Feb 2010 B2
7673282 Amaru et al. Mar 2010 B2
7676034 Wu et al. Mar 2010 B1
7681034 Lee et al. Mar 2010 B1
7681140 Ebert Mar 2010 B2
7685561 Deem et al. Mar 2010 B2
7685577 Pace et al. Mar 2010 B2
7693593 Ishibashi et al. Apr 2010 B2
7698398 Lai Apr 2010 B1
7702639 Stanley et al. Apr 2010 B2
7707224 Chastagnol et al. Apr 2010 B2
7711995 Morris May 2010 B1
7712029 Ferreira et al. May 2010 B2
7716242 Pae et al. May 2010 B2
7725474 Tamai et al. May 2010 B2
7725875 Waldrep May 2010 B2
7729940 Harvey et al. Jun 2010 B2
7730142 Levasseur et al. Jun 2010 B2
7752124 Green et al. Jul 2010 B2
7756826 Bots et al. Jul 2010 B2
7756987 Wang et al. Jul 2010 B2
7761586 Olenick et al. Jul 2010 B2
7774745 Fildebrandt et al. Aug 2010 B2
7788212 Beckmann et al. Aug 2010 B2
7788222 Shah et al. Aug 2010 B2
7788632 Kuester et al. Aug 2010 B2
7788726 Teixeira Aug 2010 B2
7797726 Ashley et al. Sep 2010 B2
7801758 Gracie et al. Sep 2010 B2
7801826 Labrou et al. Sep 2010 B2
7801912 Ransil et al. Sep 2010 B2
7802305 Leeds Sep 2010 B1
7805349 Yu et al. Sep 2010 B2
7805451 Hosokawa Sep 2010 B2
7813947 Deangelis et al. Oct 2010 B2
7822620 Dixon et al. Oct 2010 B2
7827523 Ahmed et al. Nov 2010 B2
7844640 Bender et al. Nov 2010 B2
7849143 Vuong Dec 2010 B2
7853468 Callahan Dec 2010 B2
7853470 Sonnleithner et al. Dec 2010 B2
7853925 Kemmler Dec 2010 B2
7860816 Fokoue-Nkoutche et al. Dec 2010 B2
7870540 Zare et al. Jan 2011 B2
7870608 Shraim et al. Jan 2011 B2
7873541 Klar et al. Jan 2011 B1
7877327 Gwiazda et al. Jan 2011 B2
7877812 Koved et al. Jan 2011 B2
7885841 King Feb 2011 B2
7890461 Oeda et al. Feb 2011 B2
7895260 Archer et al. Feb 2011 B2
7904360 Evans Mar 2011 B2
7904478 Yu et al. Mar 2011 B2
7904487 Ghatare Mar 2011 B2
7917888 Chong et al. Mar 2011 B2
7917963 Goyal et al. Mar 2011 B2
7921152 Ashley et al. Apr 2011 B2
7930197 Ozzie et al. Apr 2011 B2
7930753 Mellinger et al. Apr 2011 B2
7953725 Burris et al. May 2011 B2
7954150 Croft et al. May 2011 B2
7958087 Blumenau Jun 2011 B2
7958494 Chaar et al. Jun 2011 B2
7962900 Barraclough et al. Jun 2011 B2
7966310 Sullivan et al. Jun 2011 B2
7966599 Malasky et al. Jun 2011 B1
7966663 Strickland et al. Jun 2011 B2
7974992 Fastabend et al. Jul 2011 B2
7975000 Dixon et al. Jul 2011 B2
7991559 Dzekunov et al. Aug 2011 B2
7991747 Upadhyay et al. Aug 2011 B1
7996372 Rubel, Jr. Aug 2011 B2
8005891 Knowles et al. Aug 2011 B2
8010612 Costea et al. Aug 2011 B2
8010720 Iwaoka et al. Aug 2011 B2
8019881 Sandhu et al. Sep 2011 B2
8020206 Hubbard et al. Sep 2011 B2
8024384 Prabhakar et al. Sep 2011 B2
8032721 Murai Oct 2011 B2
8036374 Noble, Jr. Oct 2011 B2
8037409 Jacob et al. Oct 2011 B2
8041749 Beck Oct 2011 B2
8041763 Kordun et al. Oct 2011 B2
8041913 Wang Oct 2011 B2
8069161 Bugir et al. Nov 2011 B2
8069471 Boren Nov 2011 B2
8082539 Schelkogonov Dec 2011 B1
8090754 Schmidt et al. Jan 2012 B2
8095923 Harvey et al. Jan 2012 B2
8099709 Baikov et al. Jan 2012 B2
8103962 Embley et al. Jan 2012 B2
8117441 Kurien et al. Feb 2012 B2
8135815 Mayer Mar 2012 B2
8146054 Baker et al. Mar 2012 B2
8146074 Ito et al. Mar 2012 B2
8150717 Whitmore Apr 2012 B2
8156105 Altounian et al. Apr 2012 B2
8156158 Rolls et al. Apr 2012 B2
8156159 Ebrahimi et al. Apr 2012 B2
8166406 Goldfeder et al. Apr 2012 B1
8176061 Swanbeck et al. May 2012 B2
8176177 Sussman et al. May 2012 B2
8176334 Vainstein May 2012 B2
8176470 Klumpp et al. May 2012 B2
8180759 Hamzy May 2012 B2
8181151 Sedukhin et al. May 2012 B2
8185409 Putnam et al. May 2012 B2
8185497 Vermeulen et al. May 2012 B2
8196176 Berteau et al. Jun 2012 B2
8205093 Argott Jun 2012 B2
8205140 Hafeez et al. Jun 2012 B2
8214362 Djabarov Jul 2012 B1
8214803 Horii et al. Jul 2012 B2
8234377 Cohn Jul 2012 B2
8239244 Ginsberg et al. Aug 2012 B2
8250051 Bugir et al. Aug 2012 B2
8255468 Vitaldevara et al. Aug 2012 B2
8260262 Ben Ayed Sep 2012 B2
8261362 Goodwin et al. Sep 2012 B2
8266231 Golovin et al. Sep 2012 B1
8275632 Awaraji et al. Sep 2012 B2
8275793 Ahmad et al. Sep 2012 B2
8286239 Sutton Oct 2012 B1
8312549 Goldberg et al. Nov 2012 B2
8316237 Felsher et al. Nov 2012 B1
8332908 Hatakeyama et al. Dec 2012 B2
8340999 Kumaran et al. Dec 2012 B2
8341405 Meijer et al. Dec 2012 B2
8346929 Lai Jan 2013 B1
8364713 Pollard Jan 2013 B2
8370224 Grewal Feb 2013 B2
8370794 Moosmann et al. Feb 2013 B2
8380630 Felsher Feb 2013 B2
8380743 Convertino et al. Feb 2013 B2
8381180 Rostoker Feb 2013 B2
8381297 Touboul Feb 2013 B2
8386314 Kirkby et al. Feb 2013 B2
8392982 Harris et al. Mar 2013 B2
8418226 Gardner Apr 2013 B2
8423954 Ronen et al. Apr 2013 B2
8429179 Mirhaji Apr 2013 B1
8429597 Prigge Apr 2013 B2
8429630 Nickolov et al. Apr 2013 B2
8429758 Chen et al. Apr 2013 B2
8438644 Watters et al. May 2013 B2
8448252 King et al. May 2013 B1
8452693 Shah et al. May 2013 B2
8463247 Misiag Jun 2013 B2
8464311 Ashley et al. Jun 2013 B2
8468244 Redlich et al. Jun 2013 B2
8473324 Alvarez et al. Jun 2013 B2
8474012 Ahmed et al. Jun 2013 B2
8494894 Jaster et al. Jul 2013 B2
8504481 Motahari et al. Aug 2013 B2
8510199 Erlanger Aug 2013 B1
8515988 Jones et al. Aug 2013 B2
8516076 Thomas Aug 2013 B2
8527337 Lim et al. Sep 2013 B1
8533746 Nolan et al. Sep 2013 B2
8533844 Mahaffey et al. Sep 2013 B2
8538817 Wilson Sep 2013 B2
8539359 Rapaport et al. Sep 2013 B2
8539437 Finlayson et al. Sep 2013 B2
8560645 Linden et al. Oct 2013 B2
8560841 Chin et al. Oct 2013 B2
8560956 Curtis et al. Oct 2013 B2
8561100 Hu et al. Oct 2013 B2
8561153 Grason et al. Oct 2013 B2
8565729 Moseler et al. Oct 2013 B2
8566726 Dixon et al. Oct 2013 B2
8566938 Prakash et al. Oct 2013 B1
8571909 Miller et al. Oct 2013 B2
8572717 Narayanaswamy Oct 2013 B2
8578036 Holfelder et al. Nov 2013 B1
8578166 De Monseignat et al. Nov 2013 B2
8578481 Rowley Nov 2013 B2
8578501 Ogilvie Nov 2013 B1
8583694 Siegel et al. Nov 2013 B2
8583766 Dixon et al. Nov 2013 B2
8589183 Awaraji et al. Nov 2013 B2
8589372 Krislov Nov 2013 B2
8601467 Hofhansl et al. Dec 2013 B2
8601591 Krishnamurthy et al. Dec 2013 B2
8606746 Yeap et al. Dec 2013 B2
8612420 Sun et al. Dec 2013 B2
8612993 Grant et al. Dec 2013 B2
8615549 Knowles et al. Dec 2013 B2
8615731 Doshi Dec 2013 B2
8620952 Bennett et al. Dec 2013 B2
8621637 Al-Harbi et al. Dec 2013 B2
8626671 Federgreen Jan 2014 B2
8627114 Resch et al. Jan 2014 B2
8630961 Beilby et al. Jan 2014 B2
8631048 Davis et al. Jan 2014 B1
8640110 Kopp et al. Jan 2014 B2
8646072 Savant Feb 2014 B1
8650399 Le Bihan et al. Feb 2014 B2
8655939 Redlich et al. Feb 2014 B2
8656265 Paulin et al. Feb 2014 B1
8656456 Maxson et al. Feb 2014 B2
8661036 Turski et al. Feb 2014 B2
8667074 Farkas Mar 2014 B1
8667487 Boodman et al. Mar 2014 B1
8677472 Dotan et al. Mar 2014 B1
8681984 Lee et al. Mar 2014 B2
8682698 Cashman et al. Mar 2014 B2
8683201 Shaty Mar 2014 B2
8683502 Shkedi et al. Mar 2014 B2
8688601 Jaiswal Apr 2014 B2
8689292 Williams et al. Apr 2014 B2
8693689 Belenkiy et al. Apr 2014 B2
8700524 Williams et al. Apr 2014 B2
8700699 Shen et al. Apr 2014 B2
8706742 Ravid et al. Apr 2014 B1
8707451 Ture et al. Apr 2014 B2
8712813 King Apr 2014 B2
8713098 Adya et al. Apr 2014 B1
8713638 Hu et al. Apr 2014 B2
8719366 Mathew et al. May 2014 B2
8732839 Hohl May 2014 B2
8744894 Christiansen et al. Jun 2014 B2
8751285 Deb et al. Jun 2014 B2
8762406 Ho et al. Jun 2014 B2
8762413 Graham, Jr. et al. Jun 2014 B2
8763071 Sinha et al. Jun 2014 B2
8763082 Huber et al. Jun 2014 B2
8763131 Archer et al. Jun 2014 B2
8767947 Ristock et al. Jul 2014 B1
8769242 Tkac et al. Jul 2014 B2
8769412 Gill et al. Jul 2014 B2
8769671 Shraim et al. Jul 2014 B2
8776241 Zaitsev Jul 2014 B2
8788935 Hirsch et al. Jul 2014 B1
8793614 Wilson et al. Jul 2014 B2
8793650 Hilerio et al. Jul 2014 B2
8793781 Grossi et al. Jul 2014 B2
8793809 Falkenburg et al. Jul 2014 B2
8799984 Ahn Aug 2014 B2
8805707 Schumann, Jr. et al. Aug 2014 B2
8805806 Amarendran et al. Aug 2014 B2
8805925 Price et al. Aug 2014 B2
8812342 Barcelo et al. Aug 2014 B2
8812752 Shih et al. Aug 2014 B1
8812766 Kranendonk et al. Aug 2014 B2
8813028 Farooqi Aug 2014 B2
8813214 McNair et al. Aug 2014 B1
8819253 Simeloff et al. Aug 2014 B2
8819617 Koenig et al. Aug 2014 B1
8819800 Gao et al. Aug 2014 B2
8826446 Liu et al. Sep 2014 B1
8832649 Bishop et al. Sep 2014 B2
8832854 Staddon et al. Sep 2014 B1
8839232 Taylor et al. Sep 2014 B2
8839346 Murgia et al. Sep 2014 B2
8843487 McGraw et al. Sep 2014 B2
8843745 Roberts, Jr. Sep 2014 B2
8849757 Kruglick Sep 2014 B2
8856534 Khosravi et al. Oct 2014 B2
8856936 Datta et al. Oct 2014 B2
8862507 Sandhu et al. Oct 2014 B2
8863261 Yang Oct 2014 B2
8875232 Blom et al. Oct 2014 B2
8893078 Schaude et al. Nov 2014 B2
8893286 Oliver Nov 2014 B1
8893297 Eversoll et al. Nov 2014 B2
8904494 Kindler et al. Dec 2014 B2
8914263 Shimada et al. Dec 2014 B2
8914299 Pesci-Anderson et al. Dec 2014 B2
8914342 Kalaboukis et al. Dec 2014 B2
8914902 Moritz et al. Dec 2014 B2
8918306 Cashman et al. Dec 2014 B2
8918392 Brooker et al. Dec 2014 B1
8918632 Sartor Dec 2014 B1
8924388 Elliot et al. Dec 2014 B2
8930364 Brooker et al. Jan 2015 B1
8930896 Wiggins Jan 2015 B1
8930897 Nassar Jan 2015 B2
8935198 Phillips et al. Jan 2015 B1
8935266 Wu Jan 2015 B2
8935342 Patel Jan 2015 B2
8935804 Clark et al. Jan 2015 B1
8938221 Brazier et al. Jan 2015 B2
8943076 Stewart et al. Jan 2015 B2
8943548 Drokov et al. Jan 2015 B2
8943602 Roy et al. Jan 2015 B2
8949137 Crapo et al. Feb 2015 B2
8955038 Nicodemus et al. Feb 2015 B2
8959568 Hudis et al. Feb 2015 B2
8959584 Piliouras Feb 2015 B2
8966575 McQuay et al. Feb 2015 B2
8966597 Saylor et al. Feb 2015 B1
8973108 Roth et al. Mar 2015 B1
8977234 Chava Mar 2015 B2
8977643 Schindlauer et al. Mar 2015 B2
8978158 Rajkumar et al. Mar 2015 B2
8983972 Kriebel et al. Mar 2015 B2
8984031 Todd Mar 2015 B1
8990933 Magdalin Mar 2015 B1
8996417 Channakeshava Mar 2015 B1
8996480 Agarwala et al. Mar 2015 B2
8997213 Papakipos et al. Mar 2015 B2
9001673 Birdsall et al. Apr 2015 B2
9002939 Laden et al. Apr 2015 B2
9003295 Baschy Apr 2015 B2
9003552 Goodwin et al. Apr 2015 B2
9009851 Droste et al. Apr 2015 B2
9014661 Decharms Apr 2015 B2
9015796 Fujioka Apr 2015 B1
9021469 Hilerio et al. Apr 2015 B2
9026526 Bau et al. May 2015 B1
9030987 Bianchetti et al. May 2015 B2
9032067 Prasad et al. May 2015 B2
9043217 Cashman et al. May 2015 B2
9043480 Barton et al. May 2015 B2
9047463 Porras Jun 2015 B2
9047582 Hutchinson et al. Jun 2015 B2
9047583 Patton et al. Jun 2015 B2
9047639 Quintiliani et al. Jun 2015 B1
9049244 Prince et al. Jun 2015 B2
9049314 Pugh et al. Jun 2015 B2
9055071 Gates et al. Jun 2015 B1
9058590 Criddle et al. Jun 2015 B2
9064033 Jin et al. Jun 2015 B2
9069940 Hars Jun 2015 B2
9076231 Hill et al. Jul 2015 B1
9077736 Werth et al. Jul 2015 B2
9081952 Sagi et al. Jul 2015 B2
9087090 Cormier et al. Jul 2015 B1
9092796 Eversoll et al. Jul 2015 B2
9094434 Williams et al. Jul 2015 B2
9098515 Richter et al. Aug 2015 B2
9100778 Stogaitis et al. Aug 2015 B2
9106691 Burger et al. Aug 2015 B1
9106710 Feimster Aug 2015 B1
9110918 Rajaa et al. Aug 2015 B1
9111105 Barton et al. Aug 2015 B2
9111295 Tietzen et al. Aug 2015 B2
9123330 Sharifi et al. Sep 2015 B1
9123339 Shaw et al. Sep 2015 B1
9129311 Schoen et al. Sep 2015 B2
9135261 Maunder et al. Sep 2015 B2
9135444 Carter et al. Sep 2015 B2
9141823 Dawson Sep 2015 B2
9141911 Zhao et al. Sep 2015 B2
9152818 Hathaway et al. Oct 2015 B1
9152820 Pauley, Jr. et al. Oct 2015 B1
9154514 Prakash Oct 2015 B1
9154556 Dotan et al. Oct 2015 B1
9158655 Wadhwani et al. Oct 2015 B2
9165036 Mehra Oct 2015 B2
9170996 Lovric et al. Oct 2015 B2
9172706 Krishnamurthy et al. Oct 2015 B2
9177293 Gagnon et al. Nov 2015 B1
9178901 Xue et al. Nov 2015 B2
9183100 Gventer et al. Nov 2015 B2
9189642 Perlman Nov 2015 B2
9201572 Lyon et al. Dec 2015 B2
9201770 Duerk Dec 2015 B1
9202026 Reeves Dec 2015 B1
9202085 Mawdsley et al. Dec 2015 B2
9215076 Roth et al. Dec 2015 B1
9215252 Smith et al. Dec 2015 B2
9218596 Ronca et al. Dec 2015 B2
9224009 Liu et al. Dec 2015 B1
9230036 Davis Jan 2016 B2
9231935 Bridge et al. Jan 2016 B1
9232040 Barash et al. Jan 2016 B2
9235476 McHugh et al. Jan 2016 B2
9240987 Barrett-Bowen et al. Jan 2016 B2
9241259 Daniela et al. Jan 2016 B2
9245126 Christodorescu et al. Jan 2016 B2
9245266 Hardt Jan 2016 B2
9253609 Hosier, Jr. Feb 2016 B2
9258116 Moskowitz et al. Feb 2016 B2
9264443 Weisman Feb 2016 B2
9274858 Milliron et al. Mar 2016 B2
9280581 Grimes et al. Mar 2016 B1
9286149 Sampson et al. Mar 2016 B2
9286282 Ling, III et al. Mar 2016 B2
9288118 Pattan Mar 2016 B1
9288556 Kim et al. Mar 2016 B2
9294498 Yampolskiy et al. Mar 2016 B1
9299050 Stiffler et al. Mar 2016 B2
9306939 Chan et al. Apr 2016 B2
9317697 Maier et al. Apr 2016 B2
9317715 Schuette et al. Apr 2016 B2
9325731 McGeehan Apr 2016 B2
9336184 Mital et al. May 2016 B2
9336220 Li et al. May 2016 B2
9336324 Lomme et al. May 2016 B2
9336332 Davis et al. May 2016 B2
9336400 Milman et al. May 2016 B2
9338188 Ahn May 2016 B1
9342706 Chawla et al. May 2016 B2
9344297 Shah et al. May 2016 B2
9344424 Tenenboym et al. May 2016 B2
9344484 Ferris May 2016 B2
9348802 Massand May 2016 B2
9348862 Kawecki, III May 2016 B2
9348929 Eberlein May 2016 B2
9349016 Brisebois et al. May 2016 B1
9350718 Sondhi et al. May 2016 B2
9355157 Mohammed et al. May 2016 B2
9356961 Todd et al. May 2016 B1
9361446 Demirjian et al. Jun 2016 B1
9369488 Woods et al. Jun 2016 B2
9372869 Joseph et al. Jun 2016 B2
9374693 Olincy et al. Jun 2016 B1
9384199 Thereska et al. Jul 2016 B2
9384357 Patil et al. Jul 2016 B2
9386078 Reno et al. Jul 2016 B2
9386104 Adams et al. Jul 2016 B2
9395959 Hatfield et al. Jul 2016 B2
9396332 Abrams et al. Jul 2016 B2
9401900 Levasseur et al. Jul 2016 B2
9411967 Parecki et al. Aug 2016 B2
9411982 Dippenaar et al. Aug 2016 B1
9417859 Gounares et al. Aug 2016 B2
9418221 Turgeman Aug 2016 B2
9424021 Zamir Aug 2016 B2
9424414 Demirjian et al. Aug 2016 B1
9426177 Wang et al. Aug 2016 B2
9450940 Belov et al. Sep 2016 B2
9460136 Todd et al. Oct 2016 B1
9460171 Marrelli et al. Oct 2016 B2
9460307 Breslau et al. Oct 2016 B2
9461876 Van Dusen et al. Oct 2016 B2
9462009 Kolman et al. Oct 2016 B1
9465702 Gventer et al. Oct 2016 B2
9465800 Lacey Oct 2016 B2
9473446 Vijay et al. Oct 2016 B2
9473505 Asano et al. Oct 2016 B1
9473535 Sartor Oct 2016 B2
9477523 Warman et al. Oct 2016 B1
9477660 Scott et al. Oct 2016 B2
9477685 Leung et al. Oct 2016 B1
9477942 Adachi et al. Oct 2016 B2
9483659 Bao et al. Nov 2016 B2
9489366 Scott et al. Nov 2016 B2
9495547 Schepis et al. Nov 2016 B1
9501523 Hyatt et al. Nov 2016 B2
9507960 Bell et al. Nov 2016 B2
9509674 Nasserbakht et al. Nov 2016 B1
9509702 Grigg et al. Nov 2016 B2
9514231 Eden Dec 2016 B2
9516012 Chochois et al. Dec 2016 B2
9521166 Wilson Dec 2016 B2
9524500 Dave et al. Dec 2016 B2
9529989 Kling et al. Dec 2016 B2
9536108 Powell et al. Jan 2017 B2
9537546 Cordeiro et al. Jan 2017 B2
9542568 Francis et al. Jan 2017 B2
9549047 Fredinburg et al. Jan 2017 B1
9552395 Bayer et al. Jan 2017 B2
9552470 Turgeman et al. Jan 2017 B2
9553918 Manion et al. Jan 2017 B1
9558497 Carvalho Jan 2017 B2
9569752 Deering et al. Feb 2017 B2
9571506 Boss et al. Feb 2017 B2
9571509 Satish et al. Feb 2017 B1
9571526 Sartor Feb 2017 B2
9571559 Raleigh et al. Feb 2017 B2
9571991 Brizendine et al. Feb 2017 B1
9576289 Henderson et al. Feb 2017 B2
9578060 Brisebois et al. Feb 2017 B1
9578173 Sanghavi et al. Feb 2017 B2
9582681 Mishra Feb 2017 B2
9584964 Pelkey Feb 2017 B2
9589110 Carey et al. Mar 2017 B2
9600181 Patel et al. Mar 2017 B2
9602529 Jones et al. Mar 2017 B2
9606971 Seolas et al. Mar 2017 B2
9607041 Himmelstein Mar 2017 B2
9619652 Slater Apr 2017 B2
9619661 Finkelstein Apr 2017 B1
9621357 Williams et al. Apr 2017 B2
9621566 Gupta et al. Apr 2017 B2
9626124 Lipinski et al. Apr 2017 B2
9626680 Ryan et al. Apr 2017 B1
9629064 Graves et al. Apr 2017 B2
9642008 Wyatt et al. May 2017 B2
9646095 Gottlieb et al. May 2017 B1
9647949 Varki et al. May 2017 B2
9648036 Seiver et al. May 2017 B2
9652314 Mahiddini May 2017 B2
9654506 Barrett May 2017 B2
9654541 Kapczynski et al. May 2017 B1
9665722 Nagasundaram et al. May 2017 B2
9665733 Sills et al. May 2017 B1
9665883 Roullier et al. May 2017 B2
9672053 Tang et al. Jun 2017 B2
9672355 Titonis et al. Jun 2017 B2
9678794 Barrett et al. Jun 2017 B1
9691090 Barday Jun 2017 B1
9699209 Ng et al. Jul 2017 B2
9703549 Dufresne Jul 2017 B2
9704103 Suskind et al. Jul 2017 B2
9705840 Pujare et al. Jul 2017 B2
9705880 Siris Jul 2017 B2
9721078 Cornick et al. Aug 2017 B2
9721108 Krishnamurthy et al. Aug 2017 B2
9727751 Oliver et al. Aug 2017 B2
9729583 Barday Aug 2017 B1
9734148 Bendersky et al. Aug 2017 B2
9734255 Jiang Aug 2017 B2
9736004 Jung et al. Aug 2017 B2
9740985 Byron et al. Aug 2017 B2
9740987 Dolan Aug 2017 B2
9749408 Subramani et al. Aug 2017 B2
9754091 Kode et al. Sep 2017 B2
9756059 Demirjian et al. Sep 2017 B2
9760620 Nachnani et al. Sep 2017 B2
9760635 Bliss et al. Sep 2017 B2
9760697 Walker Sep 2017 B1
9760849 Vinnakota et al. Sep 2017 B2
9762553 Ford et al. Sep 2017 B2
9767202 Darby et al. Sep 2017 B2
9767309 Patel et al. Sep 2017 B1
9769124 Yan Sep 2017 B2
9773269 Lazarus Sep 2017 B1
9785795 Grondin et al. Oct 2017 B2
9787671 Bogrett Oct 2017 B1
9798749 Saner Oct 2017 B2
9798826 Wilson et al. Oct 2017 B2
9798896 Jakobsson Oct 2017 B2
9800605 Baikalov et al. Oct 2017 B2
9800606 Yumer Oct 2017 B1
9804649 Cohen et al. Oct 2017 B2
9804928 Davis et al. Oct 2017 B2
9805381 Frank et al. Oct 2017 B2
9811532 Parkison et al. Nov 2017 B2
9817850 Dubbels et al. Nov 2017 B2
9817978 Marsh et al. Nov 2017 B2
9819684 Cernoch et al. Nov 2017 B2
9825928 Lelcuk et al. Nov 2017 B2
9830563 Paknad Nov 2017 B2
9832633 Gerber, Jr. et al. Nov 2017 B2
9836598 Yer et al. Dec 2017 B2
9838407 Oprea et al. Dec 2017 B1
9838839 Vudali et al. Dec 2017 B2
9841969 Seibert, Jr. et al. Dec 2017 B2
9842042 Chhatwal et al. Dec 2017 B2
9842349 Sawczuk et al. Dec 2017 B2
9848005 Ardeli et al. Dec 2017 B2
9848061 Jain et al. Dec 2017 B1
9852150 Sharpe et al. Dec 2017 B2
9853959 Kapczynski et al. Dec 2017 B1
9860226 Thormaehlen Jan 2018 B2
9864735 Lamprecht Jan 2018 B1
9876825 Amar et al. Jan 2018 B2
9877138 Franklin Jan 2018 B1
9880157 Levak et al. Jan 2018 B2
9882935 Barday Jan 2018 B2
9887965 Kay et al. Feb 2018 B2
9888377 McCorkendale et al. Feb 2018 B1
9892441 Barday Feb 2018 B2
9892442 Barday Feb 2018 B2
9892443 Barday Feb 2018 B2
9892444 Barday Feb 2018 B2
9894076 Li et al. Feb 2018 B2
9898613 Swerdlow et al. Feb 2018 B1
9898739 Monastyrsky et al. Feb 2018 B2
9898769 Barday Feb 2018 B2
9912625 Mutha et al. Mar 2018 B2
9912677 Chien Mar 2018 B2
9912810 Segre et al. Mar 2018 B2
9916703 Levinson et al. Mar 2018 B2
9922124 Rathod Mar 2018 B2
9923927 McClintock et al. Mar 2018 B1
9928379 Hoffer Mar 2018 B1
9934493 Castinado et al. Apr 2018 B2
9934544 Whitfield et al. Apr 2018 B1
9936127 Todasco Apr 2018 B2
9942214 Burciu et al. Apr 2018 B1
9942244 Lahoz et al. Apr 2018 B2
9942276 Sartor Apr 2018 B2
9946897 Lovin Apr 2018 B2
9948652 Yu et al. Apr 2018 B2
9948663 Wang et al. Apr 2018 B1
9953189 Cook et al. Apr 2018 B2
9954879 Sadaghiani et al. Apr 2018 B1
9954883 Ahuja et al. Apr 2018 B2
9959551 Schermerhorn et al. May 2018 B1
9959582 Sukman et al. May 2018 B2
9961070 Tang May 2018 B2
9973518 Lee et al. May 2018 B2
9973585 Ruback et al. May 2018 B2
9977904 Khan et al. May 2018 B2
9977920 Danielson et al. May 2018 B2
9983936 Dornemann et al. May 2018 B2
9984252 Pollard May 2018 B2
9990499 Chan et al. Jun 2018 B2
9992213 Sinnema Jun 2018 B2
10001975 Bharthulwar Jun 2018 B2
10002064 Muske Jun 2018 B2
10007895 Vanasco Jun 2018 B2
10013577 Beaumont et al. Jul 2018 B1
10015164 Hamburg et al. Jul 2018 B2
10019339 Von Hanxleden et al. Jul 2018 B2
10019588 Garcia et al. Jul 2018 B2
10019591 Beguin Jul 2018 B1
10019741 Hesselink Jul 2018 B2
10021143 Cabrera et al. Jul 2018 B2
10025804 Vranyes et al. Jul 2018 B2
10025836 Batchu et al. Jul 2018 B2
10028226 Ayyagari et al. Jul 2018 B2
10032172 Barday Jul 2018 B2
10044761 Ducatel et al. Aug 2018 B2
10055426 Arasan et al. Aug 2018 B2
10055869 Borrelli et al. Aug 2018 B2
10061847 Mohammed et al. Aug 2018 B2
10069858 Robinson et al. Sep 2018 B2
10069914 Smith Sep 2018 B1
10073924 Karp et al. Sep 2018 B2
10075437 Costigan et al. Sep 2018 B1
10075451 Hall et al. Sep 2018 B1
10084817 Saher et al. Sep 2018 B2
10091214 Godlewski et al. Oct 2018 B2
10091312 Khanwalkar et al. Oct 2018 B1
10097551 Chan et al. Oct 2018 B2
10102533 Barday Oct 2018 B2
10108409 Pirzadeh et al. Oct 2018 B2
10122663 Hu et al. Nov 2018 B2
10122760 Terrill et al. Nov 2018 B2
10127403 Kong et al. Nov 2018 B2
10129211 Heath Nov 2018 B2
10140666 Wang et al. Nov 2018 B1
10142113 Zaidi et al. Nov 2018 B2
10152560 Potiagalov et al. Dec 2018 B2
10158676 Barday Dec 2018 B2
10165011 Barday Dec 2018 B2
10169762 Ogawa Jan 2019 B2
10176503 Barday et al. Jan 2019 B2
10181043 Pauley, Jr. et al. Jan 2019 B1
10181051 Barday et al. Jan 2019 B2
10187363 Smirnoff et al. Jan 2019 B2
10187394 Bar et al. Jan 2019 B2
10204154 Barday et al. Feb 2019 B2
10205994 Splaine et al. Feb 2019 B2
10212134 Rai Feb 2019 B2
10212175 Seul et al. Feb 2019 B2
10223533 Dawson Mar 2019 B2
10230571 Rangasamy et al. Mar 2019 B2
10242228 Barday et al. Mar 2019 B2
10250594 Chathoth et al. Apr 2019 B2
10255602 Wang Apr 2019 B2
10257127 Dotan-Cohen et al. Apr 2019 B2
10257181 Sherif et al. Apr 2019 B1
10268838 Yadgiri et al. Apr 2019 B2
10275221 Thattai et al. Apr 2019 B2
10275614 Barday et al. Apr 2019 B2
10282370 Barday et al. May 2019 B1
10282559 Barday et al. May 2019 B2
10284604 Barday et al. May 2019 B2
10289584 Chiba May 2019 B2
10289857 Brinskelle May 2019 B1
10289866 Barday et al. May 2019 B2
10289867 Barday et al. May 2019 B2
10289870 Barday et al. May 2019 B2
10296504 Hock et al. May 2019 B2
10304442 Rudden et al. May 2019 B1
10310723 Rathod Jun 2019 B2
10311042 Kumar Jun 2019 B1
10311475 Yuasa Jun 2019 B2
10311492 Gelfenbeyn et al. Jun 2019 B2
10318761 Barday et al. Jun 2019 B2
10320940 Brennan et al. Jun 2019 B1
10324960 Skvortsov et al. Jun 2019 B1
10326768 Verweyst et al. Jun 2019 B2
10326798 Lambert Jun 2019 B2
10326841 Bradley et al. Jun 2019 B2
10331689 Sorrentino et al. Jun 2019 B2
10331904 Sher-Jan et al. Jun 2019 B2
10333975 Soman et al. Jun 2019 B2
10346186 Kalyanpur Jul 2019 B2
10346635 Kumar et al. Jul 2019 B2
10346637 Barday et al. Jul 2019 B2
10346638 Barday et al. Jul 2019 B2
10346849 Ionescu et al. Jul 2019 B2
10348726 Caluwaert Jul 2019 B2
10348775 Barday Jul 2019 B2
10353673 Barday et al. Jul 2019 B2
10361857 Woo Jul 2019 B2
10366241 Sartor Jul 2019 B2
10373119 Driscoll et al. Aug 2019 B2
10373409 White et al. Aug 2019 B2
10375115 Mallya Aug 2019 B2
10387559 Wendt et al. Aug 2019 B1
10387577 Hill et al. Aug 2019 B2
10387657 Belfiore, Jr. et al. Aug 2019 B2
10387952 Sandhu et al. Aug 2019 B1
10395201 Vescio Aug 2019 B2
10402545 Gorfein et al. Sep 2019 B2
10404729 Turgeman Sep 2019 B2
10417401 Votaw et al. Sep 2019 B2
10417445 Wouhaybi et al. Sep 2019 B2
10417621 Cassel et al. Sep 2019 B2
10419476 Parekh Sep 2019 B2
10423985 Dutta et al. Sep 2019 B1
10425492 Comstock et al. Sep 2019 B2
10430608 Peri et al. Oct 2019 B2
10435350 Ito et al. Oct 2019 B2
10437412 Barday et al. Oct 2019 B2
10437860 Barday et al. Oct 2019 B2
10438016 Barday et al. Oct 2019 B2
10438273 Burns et al. Oct 2019 B2
10440062 Barday et al. Oct 2019 B2
10445508 Sher-Jan et al. Oct 2019 B2
10445526 Barday et al. Oct 2019 B2
10452864 Barday et al. Oct 2019 B2
10452866 Barday et al. Oct 2019 B2
10453076 Parekh et al. Oct 2019 B2
10453092 Wang et al. Oct 2019 B1
10454934 Parimi et al. Oct 2019 B2
10481763 Bartkiewicz et al. Nov 2019 B2
10489454 Chen Nov 2019 B1
10503926 Barday et al. Dec 2019 B2
10510031 Barday et al. Dec 2019 B2
10521623 Rodriguez et al. Dec 2019 B2
10534851 Chan et al. Jan 2020 B1
10535081 Ferreira et al. Jan 2020 B2
10536475 McCorkle, Jr. et al. Jan 2020 B1
10536478 Kirti et al. Jan 2020 B2
10540212 Feng et al. Jan 2020 B2
10541938 Timmerman et al. Jan 2020 B1
10546135 Kassoumeh et al. Jan 2020 B1
10552462 Hart Feb 2020 B1
10558809 Joyce et al. Feb 2020 B1
10558821 Barday et al. Feb 2020 B2
10564815 Soon-Shiong Feb 2020 B2
10564935 Barday et al. Feb 2020 B2
10564936 Barday et al. Feb 2020 B2
10565161 Barday et al. Feb 2020 B2
10565236 Barday et al. Feb 2020 B1
10567439 Barday Feb 2020 B2
10567517 Weinig et al. Feb 2020 B2
10572684 Lafever et al. Feb 2020 B2
10572686 Barday et al. Feb 2020 B2
10572778 Robinson et al. Feb 2020 B1
10574705 Barday et al. Feb 2020 B2
10581825 Poschel et al. Mar 2020 B2
10592648 Barday et al. Mar 2020 B2
10592692 Brannon et al. Mar 2020 B2
10599456 Lissack Mar 2020 B2
10606916 Brannon et al. Mar 2020 B2
10613971 Vasikarla Apr 2020 B1
10628553 Murrish et al. Apr 2020 B1
10645102 Hamdi May 2020 B2
10645548 Reynolds et al. May 2020 B2
10649630 Vora et al. May 2020 B1
10650408 Andersen et al. May 2020 B1
10657469 Bade et al. May 2020 B2
10657504 Zimmerman et al. May 2020 B1
10659566 Luah et al. May 2020 B1
10671749 Felice-Steele et al. Jun 2020 B2
10671760 Esmailzadeh et al. Jun 2020 B2
10678945 Barday et al. Jun 2020 B2
10685140 Barday et al. Jun 2020 B2
10706176 Brannon et al. Jul 2020 B2
10706226 Byun et al. Jul 2020 B2
10708305 Barday et al. Jul 2020 B2
10713387 Brannon et al. Jul 2020 B2
10726145 Duminy et al. Jul 2020 B2
10726153 Nerurkar et al. Jul 2020 B2
10726158 Brannon et al. Jul 2020 B2
10732865 Jain et al. Aug 2020 B2
10735388 Rose et al. Aug 2020 B2
10740487 Barday et al. Aug 2020 B2
10747893 Kiriyama et al. Aug 2020 B2
10747897 Cook Aug 2020 B2
10749870 Brouillette et al. Aug 2020 B2
10762213 Rudek et al. Sep 2020 B2
10762230 Ancin et al. Sep 2020 B2
10762236 Brannon Sep 2020 B2
10769302 Barday et al. Sep 2020 B2
10769303 Brannon et al. Sep 2020 B2
10776510 Antonelli et al. Sep 2020 B2
10776518 Barday et al. Sep 2020 B2
10778792 Handy et al. Sep 2020 B1
10783256 Brannon et al. Sep 2020 B2
10785173 Willett et al. Sep 2020 B2
10785299 Gupta et al. Sep 2020 B2
10791150 Barday et al. Sep 2020 B2
10795527 Legge et al. Oct 2020 B1
10796020 Barday et al. Oct 2020 B2
10796260 Brannon et al. Oct 2020 B2
10798133 Barday et al. Oct 2020 B2
10803196 Bodegas Martinez et al. Oct 2020 B2
10805331 Boyer et al. Oct 2020 B2
10831831 Greene Nov 2020 B2
10834590 Turgeman et al. Nov 2020 B2
10846433 Brannon et al. Nov 2020 B2
10853356 McPherson et al. Dec 2020 B1
10853501 Brannon Dec 2020 B2
10860721 Gentile Dec 2020 B1
10860742 Joseph et al. Dec 2020 B2
10860979 Geffen et al. Dec 2020 B2
10878127 Brannon et al. Dec 2020 B2
10885485 Brannon et al. Jan 2021 B2
10891393 Currier et al. Jan 2021 B2
10893074 Sartor Jan 2021 B2
10896394 Brannon et al. Jan 2021 B2
10902490 He et al. Jan 2021 B2
10909488 Hecht et al. Feb 2021 B2
10924514 Altman et al. Feb 2021 B1
10929557 Chavez Feb 2021 B2
10949555 Rattan et al. Mar 2021 B2
10949565 Barday et al. Mar 2021 B2
10956213 Chambers et al. Mar 2021 B1
10957326 Bhaya et al. Mar 2021 B2
10963571 Baret al. Mar 2021 B2
10963572 Belfiore, Jr. et al. Mar 2021 B2
10965547 Esposito et al. Mar 2021 B1
10970418 Durvasula et al. Apr 2021 B2
10972509 Barday et al. Apr 2021 B2
10976950 Trezzo et al. Apr 2021 B1
10983963 Venkatasubramanian et al. Apr 2021 B1
10984458 Gutierrez Apr 2021 B1
10997318 Barday et al. May 2021 B2
11003748 Oliker et al. May 2021 B2
11012475 Patnala et al. May 2021 B2
11023528 Lee et al. Jun 2021 B1
11037168 Lee et al. Jun 2021 B1
11057356 Malhotra et al. Jul 2021 B2
11057427 Wright et al. Jul 2021 B2
11062051 Barday et al. Jul 2021 B2
11068318 Kuesel et al. Jul 2021 B2
11068584 Burriesci et al. Jul 2021 B2
11068618 Brannon et al. Jul 2021 B2
11068797 Bhide et al. Jul 2021 B2
11068847 Boutros et al. Jul 2021 B2
11093950 Hersh et al. Aug 2021 B2
11138299 Brannon et al. Oct 2021 B2
11144622 Brannon et al. Oct 2021 B2
11144678 Dondini et al. Oct 2021 B2
11144862 Jackson et al. Oct 2021 B1
11195134 Brannon et al. Dec 2021 B2
11201929 Dudmesh et al. Dec 2021 B2
11210420 Brannon et al. Dec 2021 B2
11238390 Brannon et al. Feb 2022 B2
11240273 Barday et al. Feb 2022 B2
11252159 Kannan et al. Feb 2022 B2
11256777 Brannon et al. Feb 2022 B2
11263262 Chen Mar 2022 B2
11327996 Reynolds et al. May 2022 B2
11682399 Paulraj et al. Jun 2023 B2
20020004736 Roundtree et al. Jan 2002 A1
20020049907 Woods et al. Apr 2002 A1
20020055932 Wheeler et al. May 2002 A1
20020077941 Halligan et al. Jun 2002 A1
20020103854 Okita Aug 2002 A1
20020129216 Collins Sep 2002 A1
20020161594 Bryan et al. Oct 2002 A1
20020161733 Grainger Oct 2002 A1
20030041250 Proudler Feb 2003 A1
20030065641 Chaloux Apr 2003 A1
20030093680 Astley et al. May 2003 A1
20030097451 Bjorksten et al. May 2003 A1
20030097661 Li et al. May 2003 A1
20030115142 Brickell et al. Jun 2003 A1
20030130893 Farmer Jul 2003 A1
20030131001 Matsuo Jul 2003 A1
20030131093 Aschen et al. Jul 2003 A1
20030140150 Kemp et al. Jul 2003 A1
20030167216 Brown et al. Sep 2003 A1
20030212604 Cullen Nov 2003 A1
20040002818 Kulp et al. Jan 2004 A1
20040025053 Hayward Feb 2004 A1
20040088235 Ziekle et al. May 2004 A1
20040098366 Sinclair et al. May 2004 A1
20040098493 Rees May 2004 A1
20040111359 Hudock Jun 2004 A1
20040186912 Harlow et al. Sep 2004 A1
20040193907 Patanella Sep 2004 A1
20050022198 Olapurath et al. Jan 2005 A1
20050033616 Vavul et al. Feb 2005 A1
20050076294 Dehamer et al. Apr 2005 A1
20050114343 Wesinger et al. May 2005 A1
20050144066 Cope et al. Jun 2005 A1
20050197884 Mullen, Jr. Sep 2005 A1
20050198177 Black Sep 2005 A1
20050198646 Kortela Sep 2005 A1
20050246292 Sarcanin Nov 2005 A1
20050278538 Fowler Dec 2005 A1
20060031078 Pizzinger et al. Feb 2006 A1
20060035204 Lamarche et al. Feb 2006 A1
20060075122 Lindskog et al. Apr 2006 A1
20060149730 Curtis Jul 2006 A1
20060156052 Bodnar et al. Jul 2006 A1
20060190280 Hoebel et al. Aug 2006 A1
20060206375 Scott et al. Sep 2006 A1
20060224422 Cohen Oct 2006 A1
20060253597 Mujica Nov 2006 A1
20060259416 Johnson Nov 2006 A1
20070011058 Dev Jan 2007 A1
20070027715 Gropper et al. Feb 2007 A1
20070061125 Bhatt et al. Mar 2007 A1
20070061393 Moore Mar 2007 A1
20070130101 Anderson et al. Jun 2007 A1
20070130323 Landsman et al. Jun 2007 A1
20070157311 Meier et al. Jul 2007 A1
20070173355 Klein Jul 2007 A1
20070179793 Bagchi et al. Aug 2007 A1
20070180490 Renzi et al. Aug 2007 A1
20070192438 Goei Aug 2007 A1
20070266420 Hawkins et al. Nov 2007 A1
20070283171 Breslin et al. Dec 2007 A1
20080005194 Smolen et al. Jan 2008 A1
20080015927 Ramirez Jan 2008 A1
20080028065 Caso et al. Jan 2008 A1
20080028435 Strickland et al. Jan 2008 A1
20080047016 Spoonamore Feb 2008 A1
20080120699 Spear May 2008 A1
20080140696 Mathuria Jun 2008 A1
20080189306 Hewett et al. Aug 2008 A1
20080195436 Whyte Aug 2008 A1
20080222271 Spires Sep 2008 A1
20080235177 Kim et al. Sep 2008 A1
20080270203 Holmes et al. Oct 2008 A1
20080270351 Thomsen Oct 2008 A1
20080270381 Thomsen Oct 2008 A1
20080270382 Thomsen et al. Oct 2008 A1
20080270451 Thomsen et al. Oct 2008 A1
20080270462 Thomsen Oct 2008 A1
20080281649 Morris Nov 2008 A1
20080282320 Denovo et al. Nov 2008 A1
20080288271 Faust Nov 2008 A1
20080288299 Schultz Nov 2008 A1
20090012896 Arnold Jan 2009 A1
20090022301 Mudaliar Jan 2009 A1
20090037975 Ishikawa et al. Feb 2009 A1
20090119500 Roth et al. May 2009 A1
20090132419 Grammer et al. May 2009 A1
20090138276 Hayashida et al. May 2009 A1
20090140035 Miller Jun 2009 A1
20090144702 Atkin et al. Jun 2009 A1
20090158249 Tomkins et al. Jun 2009 A1
20090172705 Cheong Jul 2009 A1
20090182818 Krywaniuk Jul 2009 A1
20090187764 Astakhov et al. Jul 2009 A1
20090204452 Iskandar et al. Aug 2009 A1
20090204820 Brandenburg et al. Aug 2009 A1
20090210347 Sarcanin Aug 2009 A1
20090216610 Chorny Aug 2009 A1
20090249076 Reed et al. Oct 2009 A1
20090303237 Liu et al. Dec 2009 A1
20100010912 Jones et al. Jan 2010 A1
20100010968 Redlich et al. Jan 2010 A1
20100077484 Paretti et al. Mar 2010 A1
20100082533 Nakamura et al. Apr 2010 A1
20100094650 Tran et al. Apr 2010 A1
20100100398 Auker et al. Apr 2010 A1
20100121773 Currier et al. May 2010 A1
20100192201 Shimoni et al. Jul 2010 A1
20100205057 Hook et al. Aug 2010 A1
20100223349 Thorson Sep 2010 A1
20100228786 Török Sep 2010 A1
20100234987 Benschop et al. Sep 2010 A1
20100235297 Mamorsky Sep 2010 A1
20100235915 Memon et al. Sep 2010 A1
20100262624 Pullikottil Oct 2010 A1
20100268628 Pitkow et al. Oct 2010 A1
20100268932 Bhattacharjee Oct 2010 A1
20100281313 White et al. Nov 2010 A1
20100287114 Bartko et al. Nov 2010 A1
20100333012 Adachi et al. Dec 2010 A1
20110006996 Smith et al. Jan 2011 A1
20110010202 Neale Jan 2011 A1
20110082794 Blechman Apr 2011 A1
20110137696 Meyer et al. Jun 2011 A1
20110145154 Rivers et al. Jun 2011 A1
20110153396 Marcuvitz et al. Jun 2011 A1
20110191664 Sheleheda et al. Aug 2011 A1
20110208850 Sheleheda et al. Aug 2011 A1
20110209067 Bogess et al. Aug 2011 A1
20110231896 Tovar Sep 2011 A1
20110238573 Varadarajan Sep 2011 A1
20110252456 Hatakeyama Oct 2011 A1
20110302643 Pichna et al. Dec 2011 A1
20120041939 Amsterdamski Feb 2012 A1
20120084151 Kozak et al. Apr 2012 A1
20120084349 Lee et al. Apr 2012 A1
20120102411 Sathish Apr 2012 A1
20120102543 Kohli et al. Apr 2012 A1
20120110674 Belani et al. May 2012 A1
20120116923 Irving et al. May 2012 A1
20120131438 Li et al. May 2012 A1
20120143650 Crowley et al. Jun 2012 A1
20120144499 Tan et al. Jun 2012 A1
20120191596 Kremen et al. Jul 2012 A1
20120226621 Petran et al. Sep 2012 A1
20120239557 Weinflash et al. Sep 2012 A1
20120254320 Dove et al. Oct 2012 A1
20120259752 Agee Oct 2012 A1
20120323700 Aleksandrovich et al. Dec 2012 A1
20120330769 Arceo Dec 2012 A1
20120330869 Durham Dec 2012 A1
20130004933 Bhaskaran Jan 2013 A1
20130018954 Cheng Jan 2013 A1
20130085801 Sharpe et al. Apr 2013 A1
20130091156 Raiche et al. Apr 2013 A1
20130103485 Postrel Apr 2013 A1
20130111323 Taghaddos et al. May 2013 A1
20130124257 Schubert May 2013 A1
20130159351 Hamann et al. Jun 2013 A1
20130171968 Wang Jul 2013 A1
20130179982 Bridges et al. Jul 2013 A1
20130179988 Bekker et al. Jul 2013 A1
20130185806 Hatakeyama Jul 2013 A1
20130211872 Cherry et al. Aug 2013 A1
20130218829 Martinez Aug 2013 A1
20130219459 Bradley Aug 2013 A1
20130254139 Lei Sep 2013 A1
20130254649 O'Neill Sep 2013 A1
20130254699 Bashir et al. Sep 2013 A1
20130262328 Federgreen Oct 2013 A1
20130282438 Hunter et al. Oct 2013 A1
20130282466 Hampton Oct 2013 A1
20130290169 Bathula et al. Oct 2013 A1
20130297625 Bierner Nov 2013 A1
20130298071 Wine Nov 2013 A1
20130311224 Heroux et al. Nov 2013 A1
20130318207 Dotter Nov 2013 A1
20130326112 Park et al. Dec 2013 A1
20130332362 Ciurea Dec 2013 A1
20130340086 Blom Dec 2013 A1
20140006355 Kirihata Jan 2014 A1
20140006616 Aad et al. Jan 2014 A1
20140012833 Humprecht Jan 2014 A1
20140019561 Belity et al. Jan 2014 A1
20140032259 Lafever et al. Jan 2014 A1
20140032265 Paprocki Jan 2014 A1
20140040134 Ciurea Feb 2014 A1
20140040161 Berlin Feb 2014 A1
20140040979 Barton et al. Feb 2014 A1
20140041048 Goodwin et al. Feb 2014 A1
20140047551 Nagasundaram et al. Feb 2014 A1
20140052463 Cashman et al. Feb 2014 A1
20140067973 Eden Mar 2014 A1
20140074550 Chourey Mar 2014 A1
20140074645 Ingram Mar 2014 A1
20140075493 Krishnan et al. Mar 2014 A1
20140089027 Brown Mar 2014 A1
20140089039 McClellan Mar 2014 A1
20140108173 Cooper et al. Apr 2014 A1
20140108968 Vishria Apr 2014 A1
20140137257 Martinez et al. May 2014 A1
20140142988 Grosso et al. May 2014 A1
20140143011 Mudugu et al. May 2014 A1
20140143844 Goertzen May 2014 A1
20140164476 Thomson Jun 2014 A1
20140188956 Subba et al. Jul 2014 A1
20140196143 Fliderman et al. Jul 2014 A1
20140208418 Libin Jul 2014 A1
20140222468 Araya et al. Aug 2014 A1
20140244309 Francois Aug 2014 A1
20140244325 Cartwright Aug 2014 A1
20140244375 Kim Aug 2014 A1
20140244399 Orduna et al. Aug 2014 A1
20140257917 Spencer et al. Sep 2014 A1
20140258093 Gardiner et al. Sep 2014 A1
20140278539 Edwards Sep 2014 A1
20140278663 Samuel et al. Sep 2014 A1
20140278730 Muhart et al. Sep 2014 A1
20140278802 MacPherson Sep 2014 A1
20140283027 Orona et al. Sep 2014 A1
20140283106 Stahura et al. Sep 2014 A1
20140288971 Whibbs, III Sep 2014 A1
20140289681 Wielgosz Sep 2014 A1
20140289862 Gorfein et al. Sep 2014 A1
20140317171 Fox et al. Oct 2014 A1
20140324480 Dufel et al. Oct 2014 A1
20140337041 Madden et al. Nov 2014 A1
20140337466 Li et al. Nov 2014 A1
20140344015 Puértolas-Montañés et al. Nov 2014 A1
20150006514 Hung Jan 2015 A1
20150012363 Grant et al. Jan 2015 A1
20150019530 Felch Jan 2015 A1
20150026056 Calman et al. Jan 2015 A1
20150026260 Worthley Jan 2015 A1
20150033112 Norwood et al. Jan 2015 A1
20150066577 Christiansen et al. Mar 2015 A1
20150066865 Yara et al. Mar 2015 A1
20150088598 Acharyya et al. Mar 2015 A1
20150106260 Andrews et al. Apr 2015 A1
20150106264 Johnson Apr 2015 A1
20150106867 Liang Apr 2015 A1
20150106948 Holman et al. Apr 2015 A1
20150106949 Holman et al. Apr 2015 A1
20150121462 Courage et al. Apr 2015 A1
20150143258 Carolan et al. May 2015 A1
20150149362 Baum et al. May 2015 A1
20150154520 Federgreen et al. Jun 2015 A1
20150169318 Nash Jun 2015 A1
20150172296 Fujioka Jun 2015 A1
20150178740 Borawski et al. Jun 2015 A1
20150199534 Francis et al. Jul 2015 A1
20150199541 Koch et al. Jul 2015 A1
20150199702 Singh Jul 2015 A1
20150229664 Hawthorn et al. Aug 2015 A1
20150235049 Cohen et al. Aug 2015 A1
20150235050 Wouhaybi et al. Aug 2015 A1
20150235283 Nishikawa Aug 2015 A1
20150242773 Major et al. Aug 2015 A1
20150242778 Wilcox et al. Aug 2015 A1
20150242858 Smith et al. Aug 2015 A1
20150248391 Watanabe Sep 2015 A1
20150254597 Jahagirdar Sep 2015 A1
20150261887 Joukov Sep 2015 A1
20150262189 Vergeer Sep 2015 A1
20150264417 Spitz et al. Sep 2015 A1
20150269384 Holman et al. Sep 2015 A1
20150271167 Kalai Sep 2015 A1
20150288715 Hotchkiss Oct 2015 A1
20150309813 Patel Oct 2015 A1
20150310227 Ishida et al. Oct 2015 A1
20150310575 Shelton Oct 2015 A1
20150348200 Fair et al. Dec 2015 A1
20150356362 Demos Dec 2015 A1
20150379430 Dirac et al. Dec 2015 A1
20160006760 Lala, I et al. Jan 2016 A1
20160012465 Sharp Jan 2016 A1
20160026394 Goto Jan 2016 A1
20160034918 Bjelajac et al. Feb 2016 A1
20160048700 Stransky-Heilkron Feb 2016 A1
20160050213 Storr Feb 2016 A1
20160063523 Nistor et al. Mar 2016 A1
20160063567 Srivastava Mar 2016 A1
20160071112 Unser Mar 2016 A1
20160080405 Schler et al. Mar 2016 A1
20160099963 Mahaffey et al. Apr 2016 A1
20160103963 Mishra Apr 2016 A1
20160125550 Joao et al. May 2016 A1
20160125749 Delacroix et al. May 2016 A1
20160125751 Barker et al. May 2016 A1
20160140466 Sidebottom et al. May 2016 A1
20160143570 Valacich et al. May 2016 A1
20160148143 Anderson et al. May 2016 A1
20160162269 Pogorelik et al. Jun 2016 A1
20160164915 Cook Jun 2016 A1
20160180386 Konig Jun 2016 A1
20160188450 Appusamy et al. Jun 2016 A1
20160189156 Kim et al. Jun 2016 A1
20160196189 Miyagi et al. Jul 2016 A1
20160225000 Glasgow Aug 2016 A1
20160232465 Kurtz et al. Aug 2016 A1
20160232534 Lacey et al. Aug 2016 A1
20160234319 Griffin Aug 2016 A1
20160253497 Christodorescu et al. Sep 2016 A1
20160255139 Rathod Sep 2016 A1
20160261631 Mssamsetty et al. Sep 2016 A1
20160262163 Gonzalez Garrido et al. Sep 2016 A1
20160292453 Patterson et al. Oct 2016 A1
20160292621 Ciccone et al. Oct 2016 A1
20160321582 Broudou et al. Nov 2016 A1
20160321748 Mahatma et al. Nov 2016 A1
20160330237 Edlabadkar Nov 2016 A1
20160335531 Mullen et al. Nov 2016 A1
20160342811 Whitcomb et al. Nov 2016 A1
20160359861 Manov et al. Dec 2016 A1
20160364736 Maugans, III Dec 2016 A1
20160370954 Burningham et al. Dec 2016 A1
20160378762 Rohter Dec 2016 A1
20160381064 Chan et al. Dec 2016 A1
20160381560 Margaliot Dec 2016 A1
20170004055 Horan et al. Jan 2017 A1
20170032395 Kaufman et al. Feb 2017 A1
20170032408 Kumar et al. Feb 2017 A1
20170034101 Kumar et al. Feb 2017 A1
20170041324 Ionutescu et al. Feb 2017 A1
20170046399 Sankaranarasimhan et al. Feb 2017 A1
20170046753 Deupree, IV Feb 2017 A1
20170061501 Horwich Mar 2017 A1
20170068785 Experton et al. Mar 2017 A1
20170070495 Cherry et al. Mar 2017 A1
20170075513 Watson et al. Mar 2017 A1
20170093917 Chandra et al. Mar 2017 A1
20170115864 Thomas et al. Apr 2017 A1
20170124570 Nidamanuri et al. May 2017 A1
20170140174 Lacey et al. May 2017 A1
20170140467 Neag et al. May 2017 A1
20170142158 Laoutaris et al. May 2017 A1
20170142177 Hu May 2017 A1
20170154188 Meier et al. Jun 2017 A1
20170161520 Lockhart, III et al. Jun 2017 A1
20170171235 Mulchandani et al. Jun 2017 A1
20170171325 Perez Jun 2017 A1
20170177324 Frank et al. Jun 2017 A1
20170180378 Tyler et al. Jun 2017 A1
20170180505 Shaw et al. Jun 2017 A1
20170193017 Migliori Jul 2017 A1
20170193624 Tsai Jul 2017 A1
20170201518 Holmqvist et al. Jul 2017 A1
20170206707 Guay et al. Jul 2017 A1
20170208084 Steelman et al. Jul 2017 A1
20170213206 Shearer Jul 2017 A1
20170220685 Yan et al. Aug 2017 A1
20170220964 Datta Aug 2017 A1
20170249710 Guillama et al. Aug 2017 A1
20170269791 Meyerzon et al. Sep 2017 A1
20170270318 Ritchie Sep 2017 A1
20170278004 McElhinney et al. Sep 2017 A1
20170278117 Wallace et al. Sep 2017 A1
20170286719 Krishnamurthy et al. Oct 2017 A1
20170287031 Barday Oct 2017 A1
20170289199 Barday Oct 2017 A1
20170308875 O'Regan et al. Oct 2017 A1
20170316400 Venkatakrishnan et al. Nov 2017 A1
20170330197 DiMaggio et al. Nov 2017 A1
20170353404 Hodge Dec 2017 A1
20180032757 Michael Feb 2018 A1
20180039975 Hefetz Feb 2018 A1
20180041498 Kikuchi Feb 2018 A1
20180046753 Shelton Feb 2018 A1
20180046939 Meron et al. Feb 2018 A1
20180063174 Grill et al. Mar 2018 A1
20180063190 Wright et al. Mar 2018 A1
20180082368 Weinflash et al. Mar 2018 A1
20180083843 Sambandam Mar 2018 A1
20180091476 Jakobsson et al. Mar 2018 A1
20180131574 Jacobs et al. May 2018 A1
20180131658 Bhagwan et al. May 2018 A1
20180165637 Romero et al. Jun 2018 A1
20180198614 Neumann Jul 2018 A1
20180204281 Painter et al. Jul 2018 A1
20180219917 Chiang Aug 2018 A1
20180239500 Allen et al. Aug 2018 A1
20180248914 Sartor Aug 2018 A1
20180285887 Maung Oct 2018 A1
20180301222 Dew, Sr. et al. Oct 2018 A1
20180307859 Lafever et al. Oct 2018 A1
20180336509 Guttmann Nov 2018 A1
20180343215 Ganapathi et al. Nov 2018 A1
20180349583 Turgeman et al. Dec 2018 A1
20180351888 Howard Dec 2018 A1
20180352003 Winn et al. Dec 2018 A1
20180357243 Yoon Dec 2018 A1
20180365720 Goldman et al. Dec 2018 A1
20180374030 Barday et al. Dec 2018 A1
20180375814 Hart Dec 2018 A1
20190005210 Wiederspohn et al. Jan 2019 A1
20190012211 Selvaraj Jan 2019 A1
20190012672 Francesco Jan 2019 A1
20190019184 Lacey et al. Jan 2019 A1
20190050547 Welsh et al. Feb 2019 A1
20190087570 Sloane Mar 2019 A1
20190096020 Barday et al. Mar 2019 A1
20190108353 Sadeh et al. Apr 2019 A1
20190130132 Barbas et al. May 2019 A1
20190138496 Yamaguchi May 2019 A1
20190139087 Dabbs et al. May 2019 A1
20190148003 Van Hoe May 2019 A1
20190156053 Vogel et al. May 2019 A1
20190156058 Van Dyne et al. May 2019 A1
20190171801 Barday et al. Jun 2019 A1
20190179652 Hesener et al. Jun 2019 A1
20190180051 Barday et al. Jun 2019 A1
20190182294 Rieke et al. Jun 2019 A1
20190188402 Wang et al. Jun 2019 A1
20190266200 Francolla Aug 2019 A1
20190266201 Barday et al. Aug 2019 A1
20190266350 Barday et al. Aug 2019 A1
20190266634 Axelrod Aug 2019 A1
20190268343 Barday et al. Aug 2019 A1
20190268344 Barday et al. Aug 2019 A1
20190272492 Elledge et al. Sep 2019 A1
20190294818 Barday et al. Sep 2019 A1
20190332802 Barday et al. Oct 2019 A1
20190332807 Lafever et al. Oct 2019 A1
20190333118 Crimmins et al. Oct 2019 A1
20190354709 Brinskelle Nov 2019 A1
20190356684 Sinha et al. Nov 2019 A1
20190362169 Lin et al. Nov 2019 A1
20190362268 Fogarty et al. Nov 2019 A1
20190371303 Siva Kumaran Dec 2019 A1
20190377901 Balzer et al. Dec 2019 A1
20190378073 Lopez et al. Dec 2019 A1
20190384934 Kim Dec 2019 A1
20190392162 Stern et al. Dec 2019 A1
20190392170 Barday et al. Dec 2019 A1
20190392171 Barday et al. Dec 2019 A1
20200004938 Brannon et al. Jan 2020 A1
20200020454 McGarvey et al. Jan 2020 A1
20200050966 Enuka et al. Feb 2020 A1
20200051117 Mitchell Feb 2020 A1
20200057781 McCormick Feb 2020 A1
20200074471 Adjaoute Mar 2020 A1
20200081865 Farrar et al. Mar 2020 A1
20200082270 Gu et al. Mar 2020 A1
20200090197 Rodriguez et al. Mar 2020 A1
20200092179 Chieu et al. Mar 2020 A1
20200110589 Bequet et al. Apr 2020 A1
20200110904 Shinde et al. Apr 2020 A1
20200117737 Gopalakrishnan et al. Apr 2020 A1
20200137097 Zimmermann et al. Apr 2020 A1
20200143301 Bowers May 2020 A1
20200143797 Manoharan et al. May 2020 A1
20200159952 Dain et al. May 2020 A1
20200159955 Barlik et al. May 2020 A1
20200167653 Manjunath et al. May 2020 A1
20200175424 Kursun Jun 2020 A1
20200183655 Barday et al. Jun 2020 A1
20200186355 Davies Jun 2020 A1
20200193018 Van Dyke Jun 2020 A1
20200193022 Lunsford et al. Jun 2020 A1
20200210558 Barday et al. Jul 2020 A1
20200210620 Haletky Jul 2020 A1
20200211002 Steinberg Jul 2020 A1
20200220901 Barday et al. Jul 2020 A1
20200226156 Borra et al. Jul 2020 A1
20200226196 Brannon et al. Jul 2020 A1
20200242259 Chirravuri et al. Jul 2020 A1
20200242719 Lee Jul 2020 A1
20200250342 Miller et al. Aug 2020 A1
20200252413 Buzbee et al. Aug 2020 A1
20200252817 Brouillette et al. Aug 2020 A1
20200272764 Brannon et al. Aug 2020 A1
20200285755 Kassoumeh et al. Sep 2020 A1
20200293679 Handy et al. Sep 2020 A1
20200296171 Mocanu et al. Sep 2020 A1
20200302089 Barday et al. Sep 2020 A1
20200310917 Tkachev et al. Oct 2020 A1
20200311310 Barday et al. Oct 2020 A1
20200344243 Brannon et al. Oct 2020 A1
20200356695 Brannon et al. Nov 2020 A1
20200364369 Brannon et al. Nov 2020 A1
20200372178 Barday et al. Nov 2020 A1
20200394327 Childress et al. Dec 2020 A1
20200401380 Jacobs et al. Dec 2020 A1
20200401962 Gottemukkala et al. Dec 2020 A1
20200410117 Barday et al. Dec 2020 A1
20200410131 Barday et al. Dec 2020 A1
20200410132 Brannon et al. Dec 2020 A1
20210012341 Garg et al. Jan 2021 A1
20210056569 Silberman et al. Feb 2021 A1
20210075775 Cheng et al. Mar 2021 A1
20210081567 Park et al. Mar 2021 A1
20210099449 Frederick et al. Apr 2021 A1
20210110047 Fang Apr 2021 A1
20210125089 Nickl et al. Apr 2021 A1
20210152496 Kim et al. May 2021 A1
20210174016 Fox Jun 2021 A1
20210182940 Gupta et al. Jun 2021 A1
20210224402 Sher-Jan et al. Jul 2021 A1
20210233157 Crutchfield, Jr. Jul 2021 A1
20210243595 Buck et al. Aug 2021 A1
20210248247 Poothokaran et al. Aug 2021 A1
20210256163 Fleming et al. Aug 2021 A1
20210279360 Gimenez Palop et al. Sep 2021 A1
20210288995 Attar et al. Sep 2021 A1
20210297441 Olalere Sep 2021 A1
20210303828 Lafreniere et al. Sep 2021 A1
20210312061 Schroeder et al. Oct 2021 A1
20210326786 Sun et al. Oct 2021 A1
20210328969 Gaddam et al. Oct 2021 A1
20210382949 Yastrebenetsky et al. Dec 2021 A1
20210397735 Samatov et al. Dec 2021 A1
20210400018 Vettaikaran et al. Dec 2021 A1
20210406712 Bhide et al. Dec 2021 A1
20220137850 Boddu et al. May 2022 A1
20220171759 Jindal et al. Jun 2022 A1
20220217045 Blau et al. Jul 2022 A1
Foreign Referenced Citations (16)
Number Date Country
111496802 Aug 2020 CN
112115859 Dec 2020 CN
1394698 Mar 2004 EP
2031540 Mar 2009 EP
20130062500 Jun 2013 KR
2001033430 May 2001 WO
20020067158 Aug 2002 WO
20030050773 Jun 2003 WO
2005008411 Jan 2005 WO
2007002412 Jan 2007 WO
2008134203 Nov 2008 WO
2012174659 Dec 2012 WO
WO-2014000764 Jan 2014 WO
2015116905 Aug 2015 WO
2020146028 Jul 2020 WO
2022006421 Jan 2022 WO
Non-Patent Literature Citations (924)
Entry
Notice of Allowance, dated Jul. 7, 2023, from corresponding U.S. Appl. No. 17/977,285.
Office Action, dated Jun. 7, 2023, from corresponding U.S. Appl. No. 17/977,285.
Final Office Action, dated Mar. 16, 2022, from corresponding U.S. Appl. No. 17/838,939.
Final Office Action, dated Mar. 16, 2023, from corresponding U.S. Appl. No. 17/670,341.
Final Office Action, dated Mar. 16, 2023, from corresponding U.S. Appl. No. 17/836,454.
Final Office Action, dated Mar. 2, 2023, from corresponding U.S. Appl. No. 17/836,865.
Final Office Action, dated Mar. 3, 2023, from corresponding U.S. Appl. No. 17/670,354.
Final Office Action, dated Mar. 9, 2023, from corresponding U.S. Appl. No. 17/679,734.
Notice of Allowance, dated Mar. 6, 2023, from corresponding U.S. Appl. No. 17/836,430.
Office Action, dated Feb. 2, 2023, from corresponding U.S. Appl. No. 17/510,001.
Office Action, dated Jan. 19, 2023, from corresponding U.S. Appl. No. 17/205,165.
Office Action, dated Jan. 31, 2023, from corresponding U.S. Appl. No. 17/836,872.
Advisory Action, dated Jan. 13, 2021, from corresponding U.S. Appl. No. 16/808,493.
Advisory Action, dated Jan. 13, 2021, from corresponding U.S. Appl. No. 16/862,944.
Advisory Action, dated Jan. 13, 2021, from corresponding U.S. Appl. No. 16/862,948.
Advisory Action, dated Jan. 13, 2021, from corresponding U.S. Appl. No. 16/862,952.
Advisory Action, dated Jan. 6, 2021, from corresponding U.S. Appl. No. 16/808,497.
Advisory Action, dated Jun. 19, 2020, from corresponding U.S. Appl. No. 16/595,342.
Advisory Action, dated Jun. 2, 2020, from corresponding U.S. Appl. No. 16/404,491.
Advisory Action, dated May 21, 2020, from corresponding U.S. Appl. No. 16/557,392.
Final Office Action, dated Apr. 1, 2022, from corresponding U.S. Appl. No. 17/370,650.
Final Office Action, dated Apr. 23, 2020, from corresponding U.S. Appl. No. 16/572,347.
Final Office Action, dated Apr. 25, 2022, from corresponding U.S. Appl. No. 17/149,421.
Final Office Action, dated Apr. 27, 2021, from corresponding U.S. Appl. No. 17/068,454.
Final Office Action, dated Apr. 28, 2022, from corresponding U.S. Appl. No. 16/925,550.
Final Office Action, dated Apr. 5, 2022, from corresponding U.S. Appl. No. 17/013,756.
Final Office Action, dated Apr. 7, 2020, from corresponding U.S. Appl. No. 16/595,327.
Final Office Action, dated Aug. 10, 2020, from corresponding U.S. Appl. No. 16/791,589.
Final Office Action, dated Aug. 27, 2021, from corresponding U.S. Appl. No. 17/161,159.
Final Office Action, dated Aug. 28, 2020, from corresponding U.S. Appl. No. 16/410,336.
Final Office Action, dated Aug. 5, 2020, from corresponding U.S. Appl. No. 16/719,071.
Final Office Action, dated Aug. 9, 2021, from corresponding U.S. Appl. No. 17/119,080.
Final Office Action, dated Dec. 10, 2021, from corresponding U.S. Appl. No. 17/187,329.
Final Office Action, dated Dec. 7, 2020, from corresponding U.S. Appl. No. 16/862,956.
Final Office Action, dated Dec. 9, 2019, from corresponding U.S. Appl. No. 16/410,336.
Final Office Action, dated Feb. 19, 2020, from corresponding U.S. Appl. No. 16/404,491.
Final Office Action, dated Feb. 25, 2022, from corresponding U.S. Appl. No. 17/346,586.
Final Office Action, dated Feb. 3, 2020, from corresponding U.S. Appl. No. 16/557,392.
Final Office Action, dated Feb. 8, 2021, from corresponding U.S. Appl. No. 16/927,658.
Final Office Action, dated Jan. 17, 2018, from corresponding U.S. Appl. No. 15/619,278.
Final Office Action, dated Jan. 21, 2020, from corresponding U.S. Appl. No. 16/410,762.
Final Office Action, dated Jan. 23, 2018, from corresponding U.S. Appl. No. 15/619,479.
Final Office Action, dated Jan. 23, 2020, from corresponding U.S. Appl. No. 16/505,430.
Final Office Action, dated Jul. 1, 2022, from corresponding U.S. Appl. No. 17/187,329.
Final Office Action, dated Jul. 21, 2021, from corresponding U.S. Appl. No. 17/151,334.
Final Office Action, dated Jul. 6, 2022, from corresponding U.S. Appl. No. 17/200,698.
Final Office Action, dated Jul. 7, 2021, from corresponding U.S. Appl. No. 17/149,421.
Final Office Action, dated Jun. 10, 2022, from corresponding U.S. Appl. No. 17/161,159.
Final Office Action, dated Jun. 29, 2022, from corresponding U.S. Appl. No. 17/020,275.
Final Office Action, dated Jun. 9, 2022, from corresponding U.S. Appl. No. 17/494,220.
Final Office Action, dated Mar. 21, 2022, from corresponding U.S. Appl. No. 17/373,444.
Final Office Action, dated Mar. 22, 2022, from corresponding U.S. Appl. No. 17/380,485.
Final Office Action, dated Mar. 26, 2021, from corresponding U.S. Appl. No. 17/020,275.
Final Office Action, dated Mar. 5, 2019, from corresponding U.S. Appl. No. 16/055,961.
Final Office Action, dated Mar. 6, 2020, from corresponding U.S. Appl. No. 16/595,342.
Final Office Action, dated May 12, 2022, from corresponding U.S. Appl. No. 17/499,624.
Final Office Action, dated May 14, 2021, from corresponding U.S. Appl. No. 17/013,756.
Final Office Action, dated May 16, 2022, from corresponding U.S. Appl. No. 17/480,377.
Final Office Action, dated May 2, 2022, from corresponding U.S. Appl. No. 17/499,595.
Final Office Action, dated May 24, 2022, from corresponding U.S. Appl. No. 17/499,582.
Final Office Action, dated Nov. 29, 2017, from corresponding U.S. Appl. No. 15/619,237.
Final Office Action, dated Oct. 26, 2021, from corresponding U.S. Appl. No. 17/306,496.
Office Action, dated Oct. 26, 2018, from corresponding U.S. Appl. No. 16/041,468.
Office Action, dated Oct. 8, 2019, from corresponding U.S. Appl. No. 16/552,765.
Office Action, dated Sep. 1, 2017, from corresponding U.S. Appl. No. 15/619,459.
Office Action, dated Sep. 11, 2017, from corresponding U.S. Appl. No. 15/619,375.
Office Action, dated Sep. 11, 2017, from corresponding U.S. Appl. No. 15/619,478.
Office Action, dated Sep. 15, 2021, from corresponding U.S. Appl. No. 16/623,157.
Office Action, dated Sep. 16, 2019, from corresponding U.S. Appl. No. 16/277,715.
Office Action, dated Sep. 19, 2017, from corresponding U.S. Appl. No. 15/671,073.
Office Action, dated Sep. 2, 2022, from corresponding U.S. Appl. No. 17/499,624.
Office Action, dated Sep. 22, 2017, from corresponding U.S. Appl. No. 15/619,278.
Office Action, dated Sep. 24, 2021, from corresponding U.S. Appl. No. 17/342,153.
Office Action, dated Sep. 4, 2020, from corresponding U.S. Appl. No. 16/989,086.
Office Action, dated Sep. 5, 2017, from corresponding U.S. Appl. No. 15/619,469.
Office Action, dated Sep. 6, 2017, from corresponding U.S. Appl. No. 15/619,479.
Office Action, dated Sep. 7, 2017, from corresponding U.S. Appl. No. 15/633,703.
Office Action, dated Sep. 8, 2017, from corresponding U.S. Appl. No. 15/619,251.
Office Action, dated Sep. 8, 2022, from corresponding U.S. Appl. No. 17/850,244.
Restriction Requirement, dated Apr. 10, 2019, from corresponding U.S. Appl. No. 16/277,715.
Restriction Requirement, dated Apr. 12, 2022, from corresponding U.S. Appl. No. 17/584,187.
Restriction Requirement, dated Apr. 13, 2020, from corresponding U.S. Appl. No. 16/817,136.
Restriction Requirement, dated Apr. 24, 2019, from corresponding U.S. Appl. No. 16/278,122.
Restriction Requirement, dated Aug. 7, 2019, from corresponding U.S. Appl. No. 16/410,866.
Restriction Requirement, dated Aug. 9, 2019, from corresponding U.S. Appl. No. 16/404,399.
Restriction Requirement, dated Dec. 17, 2021, from corresponding U.S. Appl. No. 17/475,244.
Restriction Requirement, dated Dec. 31, 2018, from corresponding U.S. Appl. No. 15/169,668.
Restriction Requirement, dated Dec. 9, 2019, from corresponding U.S. Appl. No. 16/565,395.
Restriction Requirement, dated Jan. 18, 2017, from corresponding U.S. Appl. No. 15/256,430.
Restriction Requirement, dated Jul. 28, 2017, from corresponding U.S. Appl. No. 15/169,658.
Restriction Requirement, dated Jun. 15, 2021, from corresponding U.S. Appl. No. 17/187,329.
Restriction Requirement, dated Jun. 15, 2021, from corresponding U.S. Appl. No. 17/222,556.
Restriction Requirement, dated Jun. 9, 2021, from corresponding U.S. Appl. No. 17/222,725.
Restriction Requirement, dated May 5, 2020, from corresponding U.S. Appl. No. 16/808,489.
Restriction Requirement, dated Nov. 10, 2021, from corresponding U.S. Appl. No. 17/366,754.
Restriction Requirement, dated Nov. 15, 2019, from corresponding U.S. Appl. No. 16/586,202.
Restriction Requirement, dated Nov. 21, 2016, from corresponding U.S. Appl. No. 15/254,901.
Restriction Requirement, dated Nov. 5, 2019, from corresponding U.S. Appl. No. 16/563,744.
Restriction Requirement, dated Oct. 17, 2018, from corresponding U.S. Appl. No. 16/055,984.
Restriction Requirement, dated Oct. 6, 2021, from corresponding U.S. Appl. No. 17/340,699.
Restriction Requirement, dated Sep. 15, 2020, from corresponding U.S. Appl. No. 16/925,628.
Restriction Requirement, dated Sep. 9, 2019, from corresponding U.S. Appl. No. 16/505,426.
Notice of Allowance, dated Apr. 12, 2017, from corresponding U.S. Appl. No. 15/256,419.
Notice of Allowance, dated Apr. 12, 2022, from corresponding U.S. Appl. No. 17/479,807.
Notice of Allowance, dated Apr. 14, 2022, from corresponding U.S. Appl. No. 17/572,276.
Notice of Allowance, dated Apr. 17, 2020, from corresponding U.S. Appl. No. 16/593,639.
Notice of Allowance, dated Apr. 19, 2021, from corresponding U.S. Appl. No. 17/164,029.
Notice of Allowance, dated Apr. 2, 2019, from corresponding U.S. Appl. No. 16/160,577.
Notice of Allowance, dated Apr. 2, 2021, from corresponding U.S. Appl. No. 17/162,006.
Notice of Allowance, dated Apr. 20, 2022, from corresponding U.S. Appl. No. 17/573,808.
Notice of Allowance, dated Apr. 22, 2021, from corresponding U.S. Appl. No. 17/163,701.
Notice of Allowance, dated Apr. 25, 2018, from corresponding U.S. Appl. No. 15/883,041.
Office Action, dated Jan. 28, 2020, from corresponding U.S. Appl. No. 16/712,104.
Office Action, dated Jan. 29, 2021, from corresponding U.S. Appl. No. 17/101,106.
Office Action, dated Jan. 31, 2022, from corresponding U.S. Appl. No. 17/493,290.
Office Action, dated Jan. 4, 2019, from corresponding U.S. Appl. No. 16/159,566.
Office Action, dated Jan. 4, 2019, from corresponding U.S. Appl. No. 16/159,628.
Office Action, dated Jan. 4, 2021, from corresponding U.S. Appl. No. 17/013,756.
Office Action, dated Jan. 4, 2022, from corresponding U.S. Appl. No. 17/480,377.
Office Action, dated Jan. 7, 2020, from corresponding U.S. Appl. No. 16/572,182.
Office Action, dated Jan. 7, 2022, from corresponding U.S. Appl. No. 17/387,421.
Office Action, dated Jul. 13, 2021, from corresponding U.S. Appl. No. 17/306,496.
Office Action, dated Jul. 15, 2021, from corresponding U.S. Appl. No. 17/020,275.
Office Action, dated Jul. 18, 2019, from corresponding U.S. Appl. No. 16/410,762.
Office Action, dated Jul. 19, 2021, from corresponding U.S. Appl. No. 17/316,179.
Office Action, dated Jul. 21, 2017, from corresponding U.S. Appl. No. 15/256,430.
Office Action, dated Jul. 21, 2021, from corresponding U.S. Appl. No. 16/901,654.
Office Action, dated Jul. 23, 2019, from corresponding U.S. Appl. No. 16/436,616.
Office Action, dated Jul. 24, 2020, from corresponding U.S. Appl. No. 16/404,491.
Office Action, dated Jul. 27, 2020, from corresponding U.S. Appl. No. 16/595,342.
Office Action, dated Jul. 27, 2022, from corresponding U.S. Appl. No. 17/831,713.
Office Action, dated Jul. 28, 2022, from corresponding U.S. Appl. No. 16/925,550.
Office Action, dated Jul. 7, 2022, from corresponding U.S. Appl. No. 17/370,650.
Office Action, dated Jun. 1, 2020, from corresponding U.S. Appl. No. 16/862,952.
Office Action, dated Jun. 1, 2022, from corresponding U.S. Appl. No. 17/306,496.
Office Action, dated Jun. 14, 2022, from corresponding U.S. Appl. No. 17/346,586.
Office Action, dated Jun. 16, 2022, from corresponding U.S. Appl. No. 17/689,683.
Office Action, dated Jun. 24, 2019, from corresponding U.S. Appl. No. 16/410,336.
Office Action, dated Jun. 24, 2021, from corresponding U.S. Appl. No. 17/234,205.
Office Action, dated Jun. 27, 2019, from corresponding U.S. Appl. No. 16/404,405.
Office Action, dated Jun. 7, 2021, from corresponding U.S. Appl. No. 17/200,698.
Office Action, dated Jun. 9, 2021, from corresponding U.S. Appl. No. 17/222,523.
Office Action, dated Mar. 1, 2022, from corresponding U.S. Appl. No. 17/119,080.
Office Action, dated Mar. 11, 2019, from corresponding U.S. Appl. No. 16/220,978.
Office Action, dated Mar. 12, 2019, from corresponding U.S. Appl. No. 16/221,153.
Office Action, dated Mar. 15, 2021, from corresponding U.S. Appl. No. 17/149,421.
Office Action, dated Mar. 16, 2020, from corresponding U.S. Appl. No. 16/719,488.
Office Action, dated Mar. 17, 2020, from corresponding U.S. Appl. No. 16/565,395.
Office Action, dated Mar. 17, 2020, from corresponding U.S. Appl. No. 16/719,071.
Office Action, dated Mar. 2, 2022, from corresponding U.S. Appl. No. 17/020,275.
Office Action, dated Mar. 2, 2022, from corresponding U.S. Appl. No. 17/161,159.
Office Action, dated Mar. 2, 2022, from corresponding U.S. Appl. No. 17/200,698.
Office Action, dated Mar. 20, 2020, from corresponding U.S. Appl. No. 16/778,709.
Office Action, dated Mar. 21, 2022, from corresponding U.S. Appl. No. 17/571,871.
Office Action, dated Mar. 22, 2022, from corresponding U.S. Appl. No. 17/187,329.
Office Action, dated Mar. 23, 2020, from corresponding U.S. Appl. No. 16/671,444.
Office Action, dated Mar. 25, 2019, from corresponding U.S. Appl. No. 16/278,121.
Office Action, dated Mar. 25, 2020, from corresponding U.S. Appl. No. 16/701,043.
Office Action, dated Mar. 25, 2020, from corresponding U.S. Appl. No. 16/791,006.
Office Action, dated Mar. 27, 2019, from corresponding U.S. Appl. No. 16/278,120.
Office Action, dated Mar. 30, 2018, from corresponding U.S. Appl. No. 15/894,890.
Office Action, dated Mar. 30, 2018, from corresponding U.S. Appl. No. 15/896,790.
Office Action, dated Mar. 30, 2021, from corresponding U.S. Appl. No. 17/151,399.
Office Action, dated Mar. 4, 2019, from corresponding U.S. Appl. No. 16/237,083.
Office Action, dated May 12, 2022, from corresponding U.S. Appl. No. 17/509,974.
Office Action, dated May 14, 2020, from corresponding U.S. Appl. No. 16/808,497.
Office Action, dated May 14, 2020, from corresponding U.S. Appl. No. 16/808,503.
Office Action, dated May 15, 2020, from corresponding U.S. Appl. No. 16/808,493.
Office Action, dated May 16, 2018, from corresponding U.S. Appl. No. 15/882,989.
Office Action, dated May 16, 2022, from corresponding U.S. Appl. No. 17/679,750.
Office Action, dated May 17, 2019, from corresponding U.S. Appl. No. 16/277,539.
Office Action, dated May 18, 2021, from corresponding U.S. Appl. No. 17/196,570.
Office Action, dated May 2, 2018, from corresponding U.S. Appl. No. 15/894,809.
Office Action, dated May 2, 2019, from corresponding U.S. Appl. No. 16/104,628.
Office Action, dated May 24, 2022, from corresponding U.S. Appl. No. 17/674,187.
Office Action, dated May 29, 2020, from corresponding U.S. Appl. No. 16/862,944.
Office Action, dated May 29, 2020, from corresponding U.S. Appl. No. 16/862,948.
Office Action, dated May 29, 2020, from corresponding U.S. Appl. No. 16/863,226.
Office Action, dated May 5, 2020, from corresponding U.S. Appl. No. 16/410,336.
Office Action, dated May 9, 2022, from corresponding U.S. Appl. No. 16/840,943.
Office Action, dated Nov. 1, 2017, from corresponding U.S. Appl. No. 15/169,658.
Office Action, dated Nov. 10, 2021, from corresponding U.S. Appl. No. 17/380,485.
Office Action, dated Nov. 10, 2021, from corresponding U.S. Appl. No. 17/409,999.
Office Action, dated Nov. 12, 2020, from corresponding U.S. Appl. No. 17/034,355.
Office Action, dated Nov. 12, 2020, from corresponding U.S. Appl. No. 17/034,772.
Office Action, dated Nov. 12, 2021, from corresponding U.S. Appl. No. 17/346,586.
Office Action, dated Nov. 12, 2021, from corresponding U.S. Appl. No. 17/373,444.
Office Action, dated Nov. 15, 2018, from corresponding U.S. Appl. No. 16/059,911.
Office Action, dated Nov. 15, 2019, from corresponding U.S. Appl. No. 16/552,758.
Office Action, dated Nov. 16, 2021, from corresponding U.S. Appl. No. 17/370,650.
Office Action, dated Nov. 16, 2021, from corresponding U.S. Appl. No. 17/486,350.
Office Action, dated Nov. 18, 2019, from corresponding U.S. Appl. No. 16/560,885.
Office Action, dated Nov. 18, 2019, from corresponding U.S. Appl. No. 16/560,889.
Office Action, dated Nov. 18, 2019, from corresponding U.S. Appl. No. 16/572,347.
Office Action, dated Nov. 19, 2019, from corresponding U.S. Appl. No. 16/595,342.
Office Action, dated Nov. 20, 2019, from corresponding U.S. Appl. No. 16/595,327.
Office Action, dated Nov. 23, 2018, from corresponding U.S. Appl. No. 16/042,673.
Office Action, dated Nov. 23, 2021, from corresponding U.S. Appl. No. 17/013,756.
Office Action, dated Nov. 24, 2020, from corresponding U.S. Appl. No. 16/925,628.
Office Action, dated Nov. 26, 2021, from corresponding U.S. Appl. No. 16/925,550.
Office Action, dated Nov. 4, 2021, from corresponding U.S. Appl. No. 17/491,906.
Office Action, dated Nov. 8, 2021, from corresponding U.S. Appl. No. 16/872,130.
Office Action, dated Oct. 10, 2018, from corresponding U.S. Appl. No. 16/041,563.
Office Action, dated Oct. 10, 2018, from corresponding U.S. Appl. No. 16/055,083.
Office Action, dated Oct. 10, 2018, from corresponding U.S. Appl. No. 16/055,944.
Office Action, dated Oct. 12, 2021, from corresponding U.S. Appl. No. 17/346,509.
Office Action, dated Oct. 14, 2020, from corresponding U.S. Appl. No. 16/927,658.
Office Action, dated Oct. 15, 2018, from corresponding U.S. Appl. No. 16/054,780.
Office Action, dated Oct. 15, 2021, from corresponding U.S. Appl. No. 16/908,081.
Office Action, dated Oct. 16, 2019, from corresponding U.S. Appl. No. 16/557,392.
Office Action, dated Oct. 16, 2020, from corresponding U.S. Appl. No. 16/808,489.
Office Action, dated Oct. 23, 2018, from corresponding U.S. Appl. No. 16/055,961.
Office Action, dated Aug. 30, 2017, from corresponding U.S. Appl. No. 15/619,382.
Office Action, dated Aug. 30, 2021, from corresponding U.S. Appl. No. 16/938,520.
Office Action, dated Aug. 4, 2022, from corresponding U.S. Appl. No. 17/828,953.
Office Action, dated Aug. 6, 2019, from corresponding U.S. Appl. No. 16/404,491.
Office Action, dated Aug. 6, 2020, from corresponding U.S. Appl. No. 16/862,956.
Office Action, dated Dec. 11, 2019, from corresponding U.S. Appl. No. 16/578,712.
Office Action, dated Dec. 13, 2021, from corresponding U.S. Appl. No. 17/476,209.
Office Action, dated Dec. 14, 2018, from corresponding U.S. Appl. No. 16/104,393.
Office Action, dated Dec. 15, 2016, from corresponding U.S. Appl. No. 15/256,419.
Office Action, dated Dec. 16, 2019, from corresponding U.S. Appl. No. 16/563,754.
Office Action, dated Dec. 16, 2019, from corresponding U.S. Appl. No. 16/565,265.
Office Action, dated Dec. 16, 2020, from corresponding U.S. Appl. No. 17/020,275.
Office Action, dated Dec. 17, 2021, from corresponding U.S. Appl. No. 17/395,759.
Office Action, dated Dec. 17, 2021, from corresponding U.S. Appl. No. 17/499,582.
Office Action, dated Dec. 18, 2020, from corresponding U.S. Appl. No. 17/030,714.
Office Action, dated Dec. 19, 2019, from corresponding U.S. Appl. No. 16/410,866.
Office Action, dated Dec. 2, 2019, from corresponding U.S. Appl. No. 16/560,963.
Office Action, dated Dec. 2, 2021, from corresponding U.S. Appl. No. 17/504,102.
Office Action, dated Dec. 23, 2019, from corresponding U.S. Appl. No. 16/593,639.
Office Action, dated Dec. 24, 2020, from corresponding U.S. Appl. No. 17/068,454.
Office Action, dated Dec. 27, 2021, from corresponding U.S. Appl. No. 17/493,332.
Office Action, dated Dec. 29, 2021, from corresponding U.S. Appl. No. 17/479,807.
Office Action, dated Dec. 3, 2018, from corresponding U.S. Appl. No. 16/055,998.
Office Action, dated Dec. 30, 2021, from corresponding U.S. Appl. No. 17/149,421.
Office Action, dated Dec. 31, 2018, from corresponding U.S. Appl. No. 16/160,577.
Office Action, dated Dec. 7, 2021, from corresponding U.S. Appl. No. 17/499,609.
Office Action, dated Dec. 8, 2020, from corresponding U.S. Appl. No. 17/013,758.
Office Action, dated Dec. 8, 2020, from corresponding U.S. Appl. No. 17/068,198.
Office Action, dated Feb. 10, 2021, from corresponding U.S. Appl. No. 16/862,944.
Office Action, dated Feb. 10, 2021, from corresponding U.S. Appl. No. 17/106,469.
Office Action, dated Feb. 15, 2019, from corresponding U.S. Appl. No. 16/220,899.
Office Action, dated Feb. 16, 2022, from corresponding U.S. Appl. No. 16/872,031.
Office Action, dated Feb. 17, 2021, from corresponding U.S. Appl. No. 16/862,948.
Office Action, dated Feb. 18, 2021, from corresponding U.S. Appl. No. 16/862,952.
Office Action, dated Feb. 2, 2021, from corresponding U.S. Appl. No. 17/101,915.
Office Action, dated Feb. 26, 2019, from corresponding U.S. Appl. No. 16/228,250.
Office Action, dated Feb. 3, 2021, from corresponding U.S. Appl. No. 17/013,757.
Office Action, dated Feb. 5, 2020, from corresponding U.S. Appl. No. 16/586,202.
Office Action, dated Feb. 6, 2020, from corresponding U.S. Appl. No. 16/707,762.
Office Action, dated Feb. 8, 2021, from corresponding U.S. Appl. No. 17/139,650.
Office Action, dated Feb. 9, 2021, from corresponding U.S. Appl. No. 16/808,493.
Office Action, dated Feb. 9, 2022, from corresponding U.S. Appl. No. 17/543,546.
Office Action, dated Jan. 14, 2022, from corresponding U.S. Appl. No. 17/499,595.
Office Action, dated Jan. 18, 2019, from corresponding U.S. Appl. No. 16/055,984.
Office Action, dated Jan. 21, 2022, from corresponding U.S. Appl. No. 17/499,624.
Office Action, dated Jan. 22, 2021, from corresponding U.S. Appl. No. 17/099,270.
Office Action, dated Jan. 24, 2020, from corresponding U.S. Appl. No. 16/505,426.
Office Action, dated Jan. 24, 2020, from corresponding U.S. Appl. No. 16/700,049.
Office Action, dated Jan. 25, 2022, from corresponding U.S. Appl. No. 17/494,220.
Office Action, dated Jan. 27, 2020, from corresponding U.S. Appl. No. 16/656,895.
Final Office Action, dated Oct. 28, 2021, from corresponding U.S. Appl. No. 17/234,205.
Final Office Action, dated Oct. 29, 2021, from corresponding U.S. Appl. No. 17/020,275.
Final Office Action, dated Sep. 17, 2021, from corresponding U.S. Appl. No. 17/200,698.
Final Office Action, dated Sep. 21, 2020, from corresponding U.S. Appl. No. 16/808,493.
Final Office Action, dated Sep. 21, 2020, from corresponding U.S. Appl. No. 16/862,944.
Final Office Action, dated Sep. 22, 2020, from corresponding U.S. Appl. No. 16/808,497.
Final Office Action, dated Sep. 23, 2020, from corresponding U.S. Appl. No. 16/862,948.
Final Office Action, dated Sep. 24, 2020, from corresponding U.S. Appl. No. 16/862,952.
Final Office Action, dated Sep. 25, 2019, from corresponding U.S. Appl. No. 16/278,119.
Final Office Action, dated Sep. 28, 2020, from corresponding U.S. Appl. No. 16/565,395.
Final Office Action, dated Sep. 8, 2020, from corresponding U.S. Appl. No. 16/410,866.
Office Action, dated Apr. 1, 2021, from corresponding U.S. Appl. No. 17/119,080.
Office Action, dated Apr. 12, 2022, from corresponding U.S. Appl. No. 17/670,341.
Office Action, dated Apr. 15, 2021, from corresponding U.S. Appl. No. 17/161,159.
Office Action, dated Apr. 18, 2018, from corresponding U.S. Appl. No. 15/894,819.
Office Action, dated Apr. 18, 2022, from corresponding U.S. Appl. No. 17/670,349.
Office Action, dated Apr. 2, 2021, from corresponding U.S. Appl. No. 17/151,334.
Office Action, dated Apr. 20, 2020, from corresponding U.S. Appl. No. 16/812,795.
Office Action, dated Apr. 22, 2019, from corresponding U.S. Appl. No. 16/241,710.
Office Action, dated Apr. 22, 2020, from corresponding U.S. Appl. No. 16/811,793.
Office Action, dated Apr. 25, 2022, from corresponding U.S. Appl. No. 17/588,645.
Office Action, dated Apr. 26, 2022, from corresponding U.S. Appl. No. 17/151,334.
Office Action, dated Apr. 28, 2020, from corresponding U.S. Appl. No. 16/798,818.
Office Action, dated Apr. 28, 2020, from corresponding U.S. Appl. No. 16/808,500.
Office Action, dated Apr. 28, 2021, from corresponding U.S. Appl. No. 16/808,497.
Office Action, dated Apr. 29, 2020, from corresponding U.S. Appl. No. 16/791,337.
Office Action, dated Apr. 5, 2019, from corresponding U.S. Appl. No. 16/278,119.
Office Action, dated Apr. 7, 2020, from corresponding U.S. Appl. No. 16/788,633.
Office Action, dated Apr. 7, 2020, from corresponding U.S. Appl. No. 16/791,589.
Office Action, dated Apr. 8, 2022, from corresponding U.S. Appl. No. 16/938,509.
Office Action, dated Aug. 12, 2022, from corresponding U.S. Appl. No. 17/679,734.
Office Action, dated Aug. 13, 2019, from corresponding U.S. Appl. No. 16/505,430.
Office Action, dated Aug. 13, 2019, from corresponding U.S. Appl. No. 16/512,033.
Office Action, dated Aug. 15, 2019, from corresponding U.S. Appl. No. 16/505,461.
Office Action, dated Aug. 17, 2022, from corresponding U.S. Appl. No. 17/373,444.
Office Action, dated Aug. 17, 2022, from corresponding U.S. Appl. No. 17/836,430.
Office Action, dated Aug. 18, 2021, from corresponding U.S. Appl. No. 17/222,725.
Office Action, dated Aug. 19, 2019, from corresponding U.S. Appl. No. 16/278,122.
Office Action, dated Aug. 19, 2022, from corresponding U.S. Appl. No. 17/584,187.
Office Action, dated Aug. 2, 2022, from corresponding U.S. Appl. No. 17/670,354.
Office Action, dated Aug. 20, 2020, from corresponding U.S. Appl. No. 16/817,136.
Office Action, dated Aug. 23, 2017, from corresponding U.S. Appl. No. 15/626,052.
Office Action, dated Aug. 24, 2017, from corresponding U.S. Appl. No. 15/169,643.
Office Action, dated Aug. 24, 2017, from corresponding U.S. Appl. No. 15/619,451.
Office Action, dated Aug. 24, 2020, from corresponding U.S. Appl. No. 16/595,327.
Office Action, dated Aug. 27, 2019, from corresponding U.S. Appl. No. 16/410,296.
Office Action, dated Aug. 27, 2021, from corresponding U.S. Appl. No. 17/187,329.
Office Action, dated Aug. 27, 2021, from corresponding U.S. Appl. No. 17/334,948.
Office Action, dated Aug. 29, 2017, from corresponding U.S. Appl. No. 15/619,237.
Office Action, dated Aug. 30, 2017, from corresponding U.S. Appl. No. 15/619,212.
Kirkham, et al, “A Personal Data Store for an Internet of Subjects,” IEEE, pp. 92-97 (Year: 2011).
Korba, Larry et al.; “Private Data Discovery for Privacy Compliance in Collaborative Environments”; Cooperative Design, Visualization, and Engineering; Springer Berlin Heidelberg; Sep. 21, 2008; pp. 142-150.
Kristian et al, “Human Facial Age Classification Using Active Shape Module, Geometrical Feature, and Support Vendor Machine on Early Growth Stage,” ISICO, 2015, pp. 1-8 (Year: 2015).
Krol, Kat, et al, Control versus Effort in Privacy Warnings for Webforms, ACM, Oct. 24, 2016, pp. 13-23.
Lamb et al, “Role-Based Access Control for Data Service Integration”, ACM, pp. 3-11 (Year: 2006).
Lasierra et al, “Data Management in Home Scenarios Using an Autonomic Ontology-Based Approach,” IEEE, pp. 94-99 (Year: 2012).
Leadbetter, et al, “Where Big Data Meets Linked Data: Applying Standard Data Models to Environmental Data Streams,” IEEE, pp. 2929-2937 (Year: 2016).
Lenzerini et al, “Ontology-based Data Management,” ACM, pp. 5-6 (Year: 2011).
Lewis, James et al, “Microservices,” Mar. 25, 2014 (Mar. 25, 2014), XP055907494, Retrieved from the Internet: https://martinfowler.com/articles/micr oservices.html. [retrieved on Mar. 31, 2022].
Li, Ninghui, et al., t-Closeness: Privacy Beyond k-Anonymity and I-Diversity, IEEE, 2014, p. 106-115.
Liu et al., “A Novel Approach for Detecting Browser-based Silent Miner,” IEEE, pp. 490-497 (Year. 2018).
Liu et al, “Cross-Geography Scientific Data Transferring Trends and Behavior,” ACM, pp. 267-278 (Year: 2018).
Liu et al, “Overview on Ontology Mapping and Approach,” IEEE, pp. 592-595 (Year: 2011).
Liu, Kun, et al, A Framework for Computing the Privacy Scores of Users in Online Social Networks, ACM Transactions on Knowledge Discovery from Data, vol. 5, No. 1, Article 6, Dec. 2010, 30 pages.
Lu et al., “An HTTP Flooding Detection Method Based on Browser Behavior,” IEEE, pp. 1151-1154 (Year. 2006).
Lu, “How Machine Learning Mitigates Racial Bias in the US Housing Market,” Available as SSRN 3489519, pp. 1-73, Nov. 2019 (Year: 2019).
Luu, et al., “Combined Local and Holistic Facial Features for Age-Determination,” 2010 11th Int. Conf. Control, Automation, Robotics and Vision, Singapore, Dec. 7, 2010, IEEE, pp. 900-904 (Year: 2010).
Maret et al., “Multimedia Information Interchange: Web Forms Meet Data Servers”, IEEE, pp. 499-505 (Year. 1999).
Martin, et al., “Hidden Surveillance by Web Sites: Web Bugs in Contemporary Use,” Communications of the ACM, vol. 46, No. 12, Dec. 2003, pp. 258-264. Internet source https://doi.org/10.1145/953460.953509. (Year: 2003).
Matte et al., “Do Cookie Banners Respect my Choice ?: Measuring Legal Compliance of Banners from IAB Europe's Transparency and Consent Framework,” 2020 IEEE Symposium on Security and Privacy (SP), 2020, pp. 791-809 (Year: 2020).
McGarth et al., “Digital Library Technology for Locating and Accessing Scientific Data”, ACM, pp. 188-194 (Year: 1999).
Mesbah et al., “Crawling Ajax-Based Web Applications Through Dynamic Analysis of User Interface State Changes,” ACM Transactions on the Web (TWEB) vol. 6, No. 1, Article 3, Mar. 2012, pp. 1-30 (Year: 2012).
Milic et al, “Comparative Analysis of Metadata Models on e-Government Open Data Platforms,” IEEE, pp. 119-130 (Year: 2021).
Moscoso-Zea et al, “Datawarehouse Design for Educational Data Mining,” IEEE, pp. 1-6 (Year: 2016).
Mudepalli et al, “An efficient data retrieval approach using blowfish encryption on cloud CipherText Retrieval in Cloud Computing” IEEE, pp. 267-271 (Year: 2017).
Mundada et al, “Half-Baked Cookies: Hardening Cookie-Based Authentication for the Modem Web,” Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, 2016, pp. 675-685 (Year: 2016).
Nemec et al, “Assessment of Query Execution Performance Using Selected Business Intelligence Tools and Experimental Agile Oriented Data Modeling Approach,” Sep. 16, 2015, IEEE, pp. 1327-1333. (Year: 2015).
Newman et al, “High Speed Scientific Data Transfers using Software Defined Networking,” ACM, pp. 1-9 (Year: 2015).
Newman, “Email Archive Overviews using Subject Indexes”, ACM, pp. 652-653, 2002 (Year: 2002).
Nishikawa, Taiji, English Translation of JP 2019154505, Aug. 27, 2019 (Year: 2019).
Niu, et al, “Achieving Data Truthfulness and Privacy Preservation in Data Markets”, IEEE Transactions On Knowledge and Data Engineering, IEEE Service Centre, Los Alamitos, CA, US, vol. 31, No. 1, Jan. 1, 2019, pp. 105-119 (Year 2019).
Notice of Filing Date for Petition for Post-Grant Review of related Patent No. 9,691,090 dated Apr. 12, 2018.
Nouwens et al, “Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence,” ACM, pp. 1-13, Apr. 25, 2020 (Year. 2020).
O'Keefe et al, “Privacy-Preserving Data Linkage Protocols,” Proceedings of the 2004 ACM Workshop on Privacy in the Electronic Society, 2004, pp. 94-102 (Year. 2004).
Olenski, Steve, For Consumers, Data Is A Matter Of Trust, CMO Network, Apr. 18, 2016, https://www.forbes.com/sites/steveolenski/2016/04/18/for-consumers-data-is-a-matter-of-trust/#2e48496278b3.
Ozdikis et al, “Tool Support for Transformation from an OWL Ontology to an HLA Object Model,” ACM, pp. 1-6 (Year: 2010).
Paes, “Student Research Abstract: Automatic Detection of Cross-Browser Incompatibilities using Machine Learning and Screenshot Similarity,” ACM, pp. 697-698, Apr. 3, 2017 (Year: 2017).
Pearson, et al, “A Model-Based Privacy Compliance Checker,” IJEBR, vol. 5, No. 2, pp. 63-83, 2009, Nov. 21, 2008. [Online]. Available: http://dx.doi.org/10.4018/jebr.2009040104 (Year: 2008).
Pechenizkiy et al., “Process Mining Online Assessment Data,” Educational Data Mining, pp. 279-288 (Year. 2009).
Petition for Post-Grant Review of related Patent No. 9,691,090 dated Mar. 27, 2018.
Petrie et al, “The Relationship between Accessibility and Usability of Websites”, ACM, pp. 397-406 (Year: 2007).
Ping et al, “Wide Area Placement of Data Replicas for Fast and Highly Available Data Access,” ACM, pp. 1-8 (Year: 2011).
Popescu-Zeletin, “The Data Access and Transfer Support in a Local Heterogeneous Network (HMINET)”, IEEE, pp. 147-152 (Year: 1979).
Porter, “De-Identified Data and Third Party Data Mining: The Risk of Re-Identification of Personal Information,” Shidler JL Com. & Tech. 5, 2008, pp. 1-9 (Year: 2008).
Pretorius, et al, “Attributing Users Based on Web Browser History,” 2017 IEEE Conference on Application, Information and Network Security (AINS), 2017, pp. 69-74 (Year: 2017).
Preuveneers et al, “Access Control with Delegated Authorization Policy Evaluation for Data-Driven Microservice Workflows,” Future Internet 2017, MDPI, pp. 1-21 (Year: 2017).
Qiu, et al, “Design and Application of Data Integration Platform Based on Web Services and XML,” IEEE, pp. 253-256 Year: 2016).
Qu et al, “Metadata Type System: Integrate Presentation, Data Models and Extraction to Enable Exploratory Browsing Interfaces,” ACM, pp. 107-116 (Year: 2014).
Radu, et al, “Analyzing Risk Evaluation Frameworks and Risk Assessment Methods,” IEEE, Dec. 12, 2020, pp. 1-6 (Year. 2020).
Rakers, “Managing Professional and Personal Sensitive Information,” ACM, pp. 9-13, Oct. 24-27, 2010 (Year. 2010).
Reardon et al, User-Level Secure Deletion on Log Structured File Systems, ACM, 2012, retrieved online on Apr. 22, 2021, pp. 1-11. Retrieved from the Internet: URL: http://citeseerx.ist.psu.edu/viewdoc/download; sessionid=450713515DC7F19F8ED09AE961D4B60E. (Year: 2012).
Regulation (EU) 2016/679, “On the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation),” Official Journal of the European Union, May 4, 2016, pp. L 119/1-L 119/88 (Year: 2016).
Roesner et al, “Detecting and Defending Against Third-Party Tracking on the Web,” 9th USENIX Symposium on Networked Systems Design and Implementation, Apr. 11, 2013, pp. 1-14, ACM (Year: 2013).
Rozepz, “What is Google Privacy Checkup? Everything You Need to Know,” Tom's Guide web post, Apr. 26, 2018, pp. 1-11 (Year: 2018).
Sachinopoulou et al, “Ontology-Based Approach for Managing Personal Health and Wellness Information,” IEEE, pp. 1802-1805 (Year: 2007).
Salim et al, “Data Retrieval and Security using Lightweight Directory Access Protocol”, IEEE, pp. 685-688 (Year. 2009).
Sanchez-Rola et al, “Can I Opt Out Yet ?: GDPR and the Global Illusion of Cookie Control,” Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security, 2019, pp. 340-351 (Year: 2019).
Santhisree, et al, “Web Usage Data Clustering Using Dbscan Algorithm and Set Similarities,” IEEE, pp. 220-224 (Year: 2010).
Sanzo et al, “Analytical Modeling of Lock-Based Concurrency Control with Arbitrary Transaction Data Access Patterns,” ACM, pp. 69-78 (Year: 2010).
Sarkar et al, “Towards Enforcement of the EU GDPR: Enabling Data Erasure,” 2018 IEEE Confs on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, Congress on Cybermatics, 2018, pp. 222-229, IEEE (Year: 2018).
Schwartz, Edward J., et al, 2010 IEEE Symposium on Security and Privacy: All You Ever Wanted to Know About Dynamic Analysis and forward Symbolic Execution (but might have been afraid to ask), Carnegie Mellon University, IEEE Computer Society, 2010, p. 317-331.
Sedinic et al, “Security Risk Management in Complex Organization,” May 29, 2015, IEEE, pp. 1331-1337 (Year: 2015)
Shahriar et al, “A Model-Based Detection of Vulnerable and Malicious Browser Extensions,” IEEE, pp. 198-207 (Year: 2013).
Shankar et al, “Doppleganger. Better Browser Privacy Without the Bother,” Proceedings of the 13th ACM Conference on Computer and Communications Security; [ACM Conference on Computer and Communications Security], New York, NY : ACM, US, Oct. 30, 2006, pp. 154-167 (Year: 2006).
Shulz et al, “Generative Data Models for Validation and Evaluation of Visualization Techniques,” ACM, pp. 1-13 (Year: 2016).
Singh, et al, “A Metadata Catalog Service for Data Intensive Applications,” ACM, pp. 1-17 (Year: 2003).
Sjosten et al, “Discovering Browser Extensions via Web Accessible Resources,” ACM, pp. 329-336, Mar. 22, 2017 (Year: 2017).
Slezak, et al, “Brighthouse: An Analytic Data Warehouse for Ad-hoc Queries,” ACM, pp. 1337-1345 (Year: 2008).
Soceanu, et al, “Managing the Privacy and Security of eHealth Data,” May 29, 2015, IEEE, pp. 1-8 (Year: 2015).
Srinivasan et al, “Descriptive Data Analysis of File Transfer Data,” ACM, pp. 1-8 (Year: 2014).
Stack Overflow, “Is there a way to force a user to scroll to the bottom of a div?,” Stack Overflow, pp. 1-11, Nov. 2013. [Online]. Available: https://stackoverflow.com/questions/2745935/is-there-a-way-to-force-a-user-to-scroll-to-the-bottom-of-a-div (Year. 2013).
Stern, Joanna, “iPhone Privacy Is Broken. . . and Apps Are to Blame”, The Wall Street Journal, wsj.com, May 31, 2019.
Strodl, et al, “Personal & SOHO Archiving,” Vienna University of Technology, Vienna, Austria, JCDL '08, Jun. 16-20, 2008, Pittsburgh, Pennsylvania, USA, pp. 115-123 (Year. 2008).
Sukumar et al, “Review on Modern Data Preprocessing Techniques in Web Usage Mining (WUM),” IEEE, 2016, pp. 64-69 (Year: 2016).
Symantec, Symantex Data Loss Prevention—Discover, monitor, and protect confidential data; 2008; Symantec Corporation; http://www.mssuk.com/images/Symantec%2014552315_IRC_BR_DLP_03.09_sngl.pdf.
Tanasa et al, “Advanced Data Preprocessing for Intersites Web Usage Mining,” IEEE, Mar. 2004, pp. 59-65 (Year: 2004).
The Cookie Collective, Optanon Cookie Policy Generator, The Cookie Collective, Year 2016, http:/web.archive.org/web/20160324062743/https:/optanon.com/.
Thomas et al, “MooM—A Prototype Framework for Management of Ontology Mappings,” IEEE, pp. 548-555 (Year. 2011).
TRUSTe Announces General Availability of Assessment Manager for Enterprises to Streamline Data Privacy Management with Automation, PRNewswire, Mar. 4, 2015.
Tsai et al, “Determinants of Intangible Assets Value: The Data Mining Approach,” Knowledge Based System, pp. 67-77 http://www.elsevier.com/locate/knosys (Year. 2012).
Tuomas Aura et al, Scanning Electronic Documents for Personally Identifiable Information, ACM, Oct. 30, 2006, retrieved online on Jun. 13, 2019, pp. 41-49. Retrieved from the Internet: URL: http://delivery.acm.org/10.1145/1180000/1179608/p41-aura.pdf? (Year. 2006).
Van Eijk et al, “The Impact of User Location on Cookie Notices (Inside and Outside of the European Union,” IEEE Security & Privacy Workshop on Technology and Consumer Protection (CONPRO '19), Jan. 1, 2019 (Year. 2019).
Vukovic et al, “Managing Enterprise IT Systems Using Online Communities,” Jul. 9, 2011, IEEE, pp. 552-559. (Year. 2011).
Wang et al, “Revealing Key Non-Financial Factors for Online Credit-Scoring in E-Financing,” 2013, IEEE, pp. 1-6 (Year: 2013).
Wang et al, “Secure and Efficient Access to Outsourced Data,” ACM, pp. 55-65 (Year: 2009).
Weaver et al, “Understanding Information Preview in Mobile Email Processing”, ACM, pp. 303-312, 2011 (Year. 2011).
Wong et al, “Ontology Mapping for the Interoperability Problem in Network Management,” IEEE, pp. 2058-2068 (Year: 2005).
Wu et al, “Data Mining with Big Data,” IEEE, Jan. 2014, pp. 97-107, vol. 26, No. 1, (Year: 2014).
www.truste.com (1), 200150207, Internet Archive Wayback Machine, www.archive.org,2_7_2015.
Xu, et al, “GatorShare: A File System Framework for High-Throughput Data Management,” ACM, pp. 776-786 (Year: 2010).
Yang et al, “DAC-MACS: Effective Data Access Control for Multiauthority Cloud Storage Systems,” IEEE, pp. 1790-1801 (Year: 2013).
Yang et al, “Mining Web Access Sequence with Improved Apriori Algorithm,” IEEE, 2017, pp. 780-784 (Year. 2017).
Ye et al, “An Evolution-Based Cache Scheme for Scalable Mobile Data Access,” ACM, pp. 1-7 (Year. 2007).
Yin et al, “Multibank Memory Optimization for Parallel Data Access in Multiple Data Arrays”, ACM, pp. 1-8 (Year: 2016).
Yiu et al, “Outsourced Similarity Search on Metric Data Assets”, IEEE, pp. 338-352 (Year. 2012).
Yu, “Using Data from Social Media Websites to Inspire the Design of Assistive Technology”, ACM, pp. 1-2 (Year: 2016).
Yu, et al, “Performance and Fairness Issues in Big Data Transfers,” ACM, pp. 9-11 (Year. 2014).
Yue et al, “An Automatic HTTP Cookie Management System,” Computer Networks, Elsevier, Amsterdam, NL, vol. 54, No. 13, Sep. 15, 2010, pp. 2182-2198 (Year: 2010).
Zannone, et al, “Maintaining Privacy on Derived Objects,” ACM, pp. 10-19 (Year. 2005).
Zeldovich, Nickolai, et al, Making Information Flow Explicit in HiStar, OSDI '06: 7th USENIX Symposium on Operating Systems Design and Implementation, USENIX Association, p. 263-278.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036890.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036893.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036901.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036913.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036920.
Written Opinion of the International Searching Authority, dated Dec. 14, 2018, from corresponding International Application No. PCT/US2018/045296.
Written Opinion of the International Searching Authority, dated Dec. 22, 2021, from corresponding International Application No. PCT/US2021/051217.
Written Opinion of the International Searching Authority, dated Feb. 11, 2022, from corresponding International Application No. PCT/US2021/053518.
Written Opinion of the Intemational Searching Authority, dated Feb. 14, 2022, from corresponding International Application No. PCT/US2021/058274.
Written Opinion of the International Searching Authority, dated Jan. 14, 2019, from corresponding International Application No. PCT/US2018/046949.
Written Opinion of the International Searching Authority, dated Jan. 5, 2022, from corresponding International Application No. PCT/US2021/050497.
Written Opinion of the International Searching Authority, dated Jan. 7, 2019, from corresponding International Application No. PCT/US2018/055772.
Written Opinion of the Intemational Searching Authority, dated Jun. 1, 2022, from corresponding International Application No. PCT/US2022/016930.
Written Opinion of the International Searching Authority, dated Jun. 21, 2017, from corresponding International Application No. PCT/US2017/025600.
Written Opinion of the International Searching Authority, dated Jun. 22, 2022, from corresponding International Application No. PCT/US2022/019358.
Written Opinion of the International Searching Authority, dated Jun. 24, 2022, from corresponding International Application No. PCT/US2022/019882.
Written Opinion of the International Searching Authority, dated Jun. 6, 2017, from corresponding International Application No. PCT/US2017/025605.
Written Opinion of the International Searching Authority, dated Mar. 14, 2019, from corresponding International Application No. PCT/US2018/055736.
Written Opinion of the International Searching Authority, dated Mar. 18, 2022, from corresponding International Application No. PCT/US2022/013733.
Written Opinion of the International Searching Authority, dated Mar. 4, 2019, from corresponding International Application No. PCT/US2018/055773.
Written Opinion of the Intemational Searching Authority, dated Mar. 4, 2019, from corresponding International Application No. PCT/US2018/055774.
Written Opinion of the International Searching Authority, dated May 12, 2022, from corresponding International Application No. PCT/US2022/015929.
Written Opinion of the International Searching Authority, dated May 17, 2022, from corresponding International Application No. PCT/US2022/015241.
Written Opinion of the International Searching Authority, dated May 19, 2022, from corresponding International Application No. PCT/US2022/015637.
Written Opinion of the International Searching Authority, dated Nov. 12, 2021, from corresponding International Application No. PCT/US2021/043481.
Written Opinion of the International Searching Authority, dated Nov. 19, 2018, from corresponding International Application No. PCT/US2018/046939.
Written Opinion of the International Searching Authority, dated Nov. 3, 2021, from corresponding International Application No. PCT/US2021/040893.
Written Opinion of the International Searching Authority, dated Nov. 3, 2021, from corresponding International Application No. PCT/US2021/044910.
Written Opinion of the International Searching Authority, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043975.
Written Opinion of the International Searching Authority, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043976.
Written Opinion of the International Searching Authority, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043977.
Written Opinion of the International Searching Authority, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/044026.
Written Opinion of the International Searching Authority, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/045240.
Written Opinion of the International Searching Authority, dated Oct. 12, 2017, from corresponding International Application No. PCT/US2017/036888.
Written Opinion of the International Searching Authority, dated Oct. 12, 2018, from corresponding International Application No. PCT/US2018/044046.
Written Opinion of the International Searching Authority, dated Oct. 16, 2018, from corresponding International Application No. PCT/US2018/045243.
Written Opinion of the International Searching Authority, dated Oct. 18, 2018, from corresponding International Application No. PCT/US2018/045249.
Written Opinion of the International Searching Authority, dated Oct. 20, 2017, from corresponding International Application No. PCT/US2017/036917.
Written Opinion of the International Searching Authority, dated Oct. 3, 2017, from corresponding International Application No. PCT/US2017/036912.
Written Opinion of the International Searching Authority, dated Sep. 1, 2017, from corresponding International Application No. PCT/US2017/036896.
Written Opinion of the International Searching Authority, dated Sep. 12, 2018, from corresponding International Application No. PCT/US2018/037504.
Written Opinion of the International Searching Authority, dated Sep. 15, 2021, from corresponding International Application No. PCT/US2021/033631.
Abdullah et al, “The Mapping Process of Unstructured Data to the Structured Data”, ACM, pp. 151-155 (Year. 2013).
Acar, Gunes, et al, The Web Never Forgets, Computer and Communications Security, ACM, Nov. 3, 2014, pp. 674-689.
Aghasian, Erfan, et al, Scoring Users' Privacy Disclosure Across Multiple Online Social Networks,IEEE Access, Multidisciplinary Rapid Review Open Access Journal, Jul. 31, 2017, vol. 5, 2017.
Agosti et al, “Access and Exchange of Hierarchically Structured Resources on the Web with the NESTOR Framework”. IEEE, pp. 659-662 (Year: 2009).
Ahmad et al, “Task-Oriented Access Model for Secure Data Sharing Over Cloud,” ACM, pp. 1-7 (Year: 2015).
Ahmad, et al, “Performance of Resource Management Algorithms for Processable Bulk Data Transfer Tasks in Grid Environments,” ACM, pp. 177-188 (Year. 2008).
Alaa et al, “Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes,” Apr. 27, 2017, IEEE, vol. 65, issue 1, pp. 207-217 (Year: 2017).
Ali et al, “Age Estimation from Facial Images Using Biometric Ratios and Wrinkle Analysis,” IEEE, 2015, pp. 1-5 (Year: 2015).
Dwork, Cynthia, Differential Privacy, Microsoft Research, p. 1-12.
Edinger et al, “Age and Gender Estimation of Unfiltered Faces,” IEEE, 2014, pp. 2170-2179 (Year: 2014).
Emerson, et al, “A Data Mining Driven Risk Profiling Method for Road Asset Management,” ACM, pp. 1267-1275 (Year: 2013).
Enck, William, et al, TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones, ACM Transactions on Computer Systems, vol. 32, No. 2, Article 5, Jun. 2014, p. 5:1-5:29.
Everypixel Team, “A New Age Recognition API Detects the Age of People on Photos, ” May 20, 2019, pp. 1-5 (Year: 2019).
Ex Parte Quayle Action, dated May 10, 2022, from corresponding U.S. Appl. No. 17/668,714.
Falbo et al, “An Ontological Approach to Domain Engineering,” ACM, pp. 351-358 (Year: 2002).
Fan et al, “Intrusion Investigations with Data-hiding for Computer Log-file Forensics,” IEEE, pp. 1-6 (Year. 2010).
Final Written Decision Regarding Post-Grant Review in Case PGR2018-00056 for U.S. Pat. No. 9,691,090 B1, Oct. 10, 2019.
Francis, Andre, Business Mathematics and Statistics, South-Western Cengage Learning, 2008, Sixth Edition.
Friedman et al, “Data Mining with Differential Privacy,” ACM, Jul. 2010, pp. 493-502 (Year. 2010).
Frikken, Keith B., et al, Yet Another Privacy Metric for Publishing Micro-data, Miami University, Oct. 27, 2008, p. 117-121.
Fung et al, “Discover Information and Knowledge from Websites using an Integrated Summarization and Visualization Framework”, IEEE, pp. 232-235 (Year: 2010).
Gajare et al, “Improved Automatic Feature Selection Approach for Health Risk Prediction,” Feb. 16, 2018, IEEE, pp. 816-819 (Year. 2018).
Geko et al, “An Ontology Capturing the Interdependence of the General Data Protection Regulation (GDPR) and Information Security,” ACM, pp. 1-6, Nov. 15-16, 2018 (Year. 2018).
Golab, et al, “Issues in Data Stream Management,” ACM, SIGMOD Record, vol. 32, No. 2, Jun. 2003, pp. 5-14 (Year: 2003).
Golfarelli et al, “Beyond Data Warehousing: What's Next in Business Intelligence?,” ACM, pp. 1-6 (Year. 2004).
Gonc̨alves et al., “The XML Log Standard for Digital Libraries: Analysis, Evolution, and Deployment,” IEEE, pp. 312-314 (Year: 2003).
Goni, Kyriaki, “Deletion Process_Only you can see my history: Investigating Digital Privacy, Digital Oblivion, and Control on Personal Data Through an Interactive Art Installation,” ACM, 2016, retrieved online on Oct. 3, 2019, pp. 324-333. Retrieved from the Internet URL: http://delivery.acm.org/10.1145/2920000/291.
Gowadia et al, “RDF Metadata for XML Access Control,” ACM, pp. 31-48 (Year: 2003).
Grolinger, et al, “Data Management in Cloud Environments: NoSQL and NewSQL Data Stores,” Journal of Cloud Computing: Advances, Systems and Applications, pp. 1-24 (Year: 2013).
Guo, et al, “Opal: A Passe-partout for Web Forms,” ACM, pp. 353-356 (Year: 2012).
Gustarini, et al, “Evaluation of Challenges in Human Subject Studies “In-the-Wild” Using Subjects' Personal Smartphones,” ACM, pp. 1447-1456 (Year. 2013).
Hacigümüs, Hakan, et al, Executing SQL over Encrypted Data in the Database Service-Provider Model, ACM, June 3. 2002, pp. 216-227.
Han et al, “Demographic Estimation from Face Images: Human vs. Machine Performance,” IEEE, 2015, pp. 1148-1161 (Year: 2015).
Hauch, et al, “Information Intelligence: Metadata for Information Discovery, Access, and Integration,” ACM, pp. 793-798 (Year. 2005).
He et al, “A Crowdsourcing Framework for Detecting of Cross-Browser Issues in Web Application,” ACM, pp. 1-4, Nov. 6, 2015 (Year: 2015).
Heil et al, “Downsizing and Rightsizing,” https://web.archive.org/web/20130523153311/https://www.referenceforbusiness.com/management/De-Ele/Downsizing-and-Rightsizing.html (Year: 2013).
Hernandez, et al, “Data Exchange with Data-Metadata Translations,” ACM, pp. 260-273 (Year: 2008).
Hinde, “A Model to Assess Organisational Information Privacy Maturity Against the Protection of Personal Information Act Dissertation University of Cape Town” 2014, pp. 1-121 (Year: 2014).
Hodge, et al, “Managing Virtual Data Marts with Metapointer Tables,” pp. 1-7 (Year: 2002).
Horrall et al, “Evaluating Risk: IBM's Country Financial Risk and Treasury Risk Scorecards,” Jul. 21, 2014, IBM, vol. 58, issue 4, pp. 2:1-2:9 (Year: 2014).
Hu, et al, “Attribute Considerations for Access Control Systems,” NIST Special Publication 800-205, Jun. 2019, pp. 1-42 (Year: 2019).
Hu, et al, “Guide to Attribute Based Access Control (ABAC) Definition and Considerations (Draft),” NIST Special Publication 800-162, pp. 1-54 (Year: 2013).
Huang, et al, “A Study on Information Security Management with Personal Data Protection,” IEEE, Dec. 9, 2011, pp. 624-630 (Year: 2011).
Huettner, “Digital Risk Management: Protecting Your Privacy, Improving Security, and Preparing for Emergencies,” IEEE, pp. 136-138 (Year. 2006).
Huner et al., “Towards a Maturity Model for Corporate Data Quality Management”, ACM, pp. 231-238, 2009 (Year: 2009).
Hunton & Williams LLP, The Role of Risk Management in Data Protection, Privacy Risk Framework and the Risk-based Approach to Privacy, Centre for Information Policy Leadership, Workshop II, Nov. 23, 2014.
Huo et al, “A Cloud Storage Architecture Model for Data-Intensive Applications,” IEEE, pp. 1-4 (Year. 2011).
Imran et al, “Searching in Cloud Object Storage by Using a Metadata Model”, IEEE, 2014, retrieved online on Apr. 1, 2020, pp. 121-128. Retrieved from the Internet: URL: https://ieeeexplore.ieee.org/stamp/stamp.jsp? (Year. 2014).
Iordanou et al., “Tracing Cross Border Web Tracking,” Oct. 31, 2018, pp. 329-342, ACM (Year: 2018).
Islam, et al, “Mixture Model Based Label Association Techniques for Web Accessibility,” ACM, pp. 67-76 (Year: 2010).
Jayasinghe et al, “Matching Facial Images Using Age Related Morphing Changes,” ISSRI, 2009, pp. 2901-2907 (Year: 2009).
Jensen, et al, “Temporal Data Management,” IEEE Transactions on Knowledge and Data Engineering, vol. 11, No. 1, Jan./Feb. 1999, pp. 36-44 (Year: 1999).
Jiahao Chen et al. “Fairness Under Unawareness: Assessing Disparity when Protected Class is Unobserved,” ARXIV.ORG, Cornell University Library, 201 Olin Library Cornell University, Ithaca, NY 14853, Nov. 27, 2018 (Nov. 27, 2018), Section 2, Figure 2. (Year 2018).
Joel Reardon et al, Secure Data Deletion from Persistent Media, ACM, Nov. 4, 2013, retrieved online on Jun. 13,2019, pp. 271-283. Retrieved from the Internet: URL: http://delivery.acm.org/10.1145/2520000/2516699/p271-reardon.pdf? (Year: 2013).
Jones et al, “AI and the Ethics of Automating Consent,” IEEE, pp. 64-72, May 2018 (Year: 2018).
Joonbakhsh et al, “Mining and Extraction of Personal Software Process measures through IDE Interaction logs,” ACM/IEEE, 2018, retrieved online on Dec. 2, 2019, pp. 78-81. Retrieved from the Internet: URL: http://delivery.acm.org/10.1145/3200000/3196462/p78-joonbakhsh.pdf? (Year. 2018).
Jun et al, “Scalable Multi-Access Flash Store for Big Data Analytics,” ACM, pp. 55-64 (Year: 2014).
Khan et al, “Wrinkles Energy Based Age Estimation Using Discrete Cosine Transform,” IEEE, 2015, pp. 1-4 (Year: 2015).
Notice of Allowance, dated Jan. 25, 2021, from corresponding U.S. Appl. No. 16/410,336.
Notice of Allowance, dated Jan. 26, 2018, from corresponding U.S. Appl. No. 15/619,469.
Notice of Allowance, dated Jan. 26, 2022, from corresponding U.S. Appl. No. 17/491,906.
Notice of Allowance, dated Jan. 29, 2020, from corresponding U.S. Appl. No. 16/278,119.
Notice of Allowance, dated Jan. 31, 2022, from corresponding U.S. Appl. No. 17/472,948.
Notice of Allowance, dated Jan. 5, 2022, from corresponding U.S. Appl. No. 17/475,241.
Notice of Allowance, dated Jan. 6, 2021, from corresponding U.S. Appl. No. 16/595,327.
Notice of Allowance, dated Jan. 6, 2022, from corresponding U.S. Appl. No. 17/407,765.
Notice of Allowance, dated Jan. 7, 2022, from corresponding U.S. Appl. No. 17/222,725.
Notice of Allowance, dated Jan. 8, 2020, from corresponding U.S. Appl. No. 16/600,879.
Notice of Allowance, dated Jul. 10, 2019, from corresponding U.S. Appl. No. 16/237,083.
Notice of Allowance, dated Jul. 10, 2019, from corresponding U.S. Appl. No. 16/403,358.
Notice of Allowance, dated Jul. 12, 2019, from corresponding U.S. Appl. No. 16/278,121.
Notice of Allowance, dated Jul. 14, 2020, from corresponding U.S. Appl. No. 16/701,043.
Notice of Allowance, dated Jul. 15, 2020, from corresponding U.S. Appl. No. 16/791,006.
Notice of Allowance, dated Jul. 16, 2020, from corresponding U.S. Appl. No. 16/901,979.
Notice of Allowance, dated Jul. 17, 2019, from corresponding U.S. Appl. No. 16/055,961.
Notice of Allowance, dated Jul. 17, 2020, from corresponding U.S. Appl. No. 16/778,709.
Notice of Allowance, dated Jul. 19, 2021, from corresponding U.S. Appl. No. 17/306,252.
Notice of Allowance, dated Jul. 20, 2022, from corresponding U.S. Appl. No. 16/938,509.
Notice of Allowance, dated Jul. 21, 2020, from corresponding U.S. Appl. No. 16/557,392.
Notice of Allowance, dated Jul. 23, 2019, from corresponding U.S. Appl. No. 16/220,978.
Notice of Allowance, dated Jul. 26, 2019, from corresponding U.S. Appl. No. 16/409,673.
Notice of Allowance, dated Jul. 26, 2021, from corresponding U.S. Appl. No. 17/151,399.
Notice of Allowance, dated Jul. 26, 2021, from corresponding U.S. Appl. No. 17/207,316.
Notice of Allowance, dated Jul. 27, 2022, from corresponding U.S. Appl. No. 17/679,750.
Notice of Allowance, dated Jul. 29, 2022, from corresponding U.S. Appl. No. 17/670,341.
Notice of Allowance, dated Jul. 31, 2019, from corresponding U.S. Appl. No. 16/221,153.
Notice of Allowance, dated Jul. 7, 2022, from corresponding U.S. Appl. No. 17/571,871.
Notice of Allowance, dated Jul. 8, 2021, from corresponding U.S. Appl. No. 17/201,040.
Notice of Allowance, dated Jun. 1, 2020, from corresponding U.S. Appl. No. 16/813,321.
Notice of Allowance, dated Jun. 11, 2021, from corresponding U.S. Appl. No. 16/862,948.
Notice of Allowance, dated Jun. 11, 2021, from corresponding U.S. Appl. No. 16/862,952.
Notice of Allowance, dated Jun. 11, 2021, from corresponding U.S. Appl. No. 17/216,436.
Notice of Allowance, dated Jun. 12, 2019, from corresponding U.S. Appl. No. 16/278,123.
Notice of Allowance, dated Jun. 12, 2019, from corresponding U.S. Appl. No. 16/363,454.
Notice of Allowance, dated Jun. 14, 2022, from corresponding U.S. Appl. No. 17/679,734.
Notice of Allowance, dated Jun. 16, 2020, from corresponding U.S. Appl. No. 16/798,818.
Notice of Allowance, dated Jun. 16, 2022, from corresponding U.S. Appl. No. 17/119,080.
Notice of Allowance, dated Jun. 17, 2020, from corresponding U.S. Appl. No. 16/656,895.
Notice of Allowance, dated Jun. 18, 2019, from corresponding U.S. Appl. No. 16/410,566.
Notice of Allowance, dated Jun. 19, 2018, from corresponding U.S. Appl. No. 15/894,890.
Notice of Allowance, dated Jun. 19, 2019, from corresponding U.S. Appl. No. 16/042,673.
Notice of Allowance, dated Jun. 19, 2019, from corresponding U.S. Appl. No. 16/055,984.
Notice of Allowance, dated Jun. 2, 2021, from corresponding U.S. Appl. No. 17/198,581.
Notice of Allowance, dated Jun. 2, 2022, from corresponding U.S. Appl. No. 17/493,290.
Notice of Allowance, dated Jun. 21, 2019, from corresponding U.S. Appl. No. 16/404,439.
Notice of Allowance, dated Jun. 22, 2020, from corresponding U.S. Appl. No. 16/791,337.
Notice of Allowance, dated Jun. 23, 2022, from corresponding U.S. Appl. No. 17/588,645.
Notice of Allowance, dated Jun. 27, 2018, from corresponding U.S. Appl. No. 15/882,989.
Notice of Allowance, dated Apr. 27, 2022, from corresponding U.S. Appl. No. 17/573,999.
Notice of Allowance, dated Apr. 28, 2021, from corresponding U.S. Appl. No. 17/135,445.
Notice of Allowance, dated Apr. 28, 2021, from corresponding U.S. Appl. No. 17/181,828.
Notice of Allowance, dated Apr. 28, 2022, from corresponding U.S. Appl. No. 17/592,922.
Notice of Allowance, dated Apr. 28, 2022, from corresponding U.S. Appl. No. 17/670,352.
Notice of Allowance, dated Apr. 29, 2020, from corresponding U.S. Appl. No. 16/700,049.
Notice of Allowance, dated Apr. 29, 2022, from corresponding U.S. Appl. No. 17/387,421.
Notice of Allowance, dated Apr. 30, 2020, from corresponding U.S. Appl. No. 16/565,265.
Notice of Allowance, dated Apr. 30, 2020, from corresponding U.S. Appl. No. 16/820,346.
Notice of Allowance, dated Apr. 30, 2021, from corresponding U.S. Appl. No. 16/410,762.
Notice of Allowance, dated Apr. 4, 2022, from corresponding U.S. Appl. No. 17/493,332.
Notice of Allowance, dated Apr. 4, 2022, from corresponding U.S. Appl. No. 17/572,298.
Notice of Allowance, dated Apr. 8, 2019, from corresponding U.S. Appl. No. 16/228,250.
Notice of Allowance, dated Apr. 8, 2020, from corresponding U.S. Appl. No. 16/791,348.
Notice of Allowance, dated Apr. 9, 2020, from corresponding U.S. Appl. No. 16/791,075.
Notice of Allowance, dated Aug. 10, 2020, from corresponding U.S. Appl. No. 16/671,444.
Notice of Allowance, dated Aug. 10, 2020, from corresponding U.S. Appl. No. 16/788,633.
Notice of Allowance, dated Aug. 12, 2020, from corresponding U.S. Appl. No. 16/719,488.
Notice of Allowance, dated Aug. 12, 2021, from corresponding U.S. Appl. No. 16/881,832.
Notice of Allowance, dated Aug. 14, 2018, from corresponding U.S. Appl. No. 15/989,416.
Notice of Allowance, dated Aug. 18, 2017, from corresponding U.S. Appl. No. 15/619,455.
Notice of Allowance, dated Aug. 20, 2019, from corresponding U.S. Appl. No. 16/241,710.
Notice of Allowance, dated Aug. 22, 2022, from corresponding U.S. Appl. No. 17/499,595.
Notice of Allowance, dated Aug. 24, 2018, from corresponding U.S. Appl. No. 15/619,479.
Notice of Allowance, dated Aug. 26, 2019, from corresponding U.S. Appl. No. 16/443,374.
Notice of Allowance, dated Aug. 26, 2020, from corresponding U.S. Appl. No. 16/808,503.
Notice of Allowance, dated Aug. 28, 2019, from corresponding U.S. Appl. No. 16/278,120.
Notice of Allowance, dated Aug. 3, 2022, from corresponding U.S. Appl. No. 17/668,714.
Notice of Allowance, dated Aug. 30, 2018, from corresponding U.S. Appl. No. 15/996,208.
Notice of Allowance, dated Aug. 31, 2021, from corresponding U.S. Appl. No. 17/326,901.
Notice of Allowance, dated Aug. 4, 2021, from corresponding U.S. Appl. No. 16/895,278.
Notice of Allowance, dated Aug. 4, 2022, from corresponding U.S. Appl. No. 17/670,349.
Notice of Allowance, dated Aug. 7, 2020, from corresponding U.S. Appl. No. 16/901,973.
Notice of Allowance, dated Aug. 9, 2018, from corresponding U.S. Appl. No. 15/882,989.
Notice of Allowance, dated Aug. 9, 2021, from corresponding U.S. Appl. No. 16/881,699.
Notice of Allowance, dated Aug. 9, 2022, from corresponding U.S. Appl. No. 17/832,313.
Notice of Allowance, dated Dec. 10, 2018, from corresponding U.S. Appl. No. 16/105,602.
Notice of Allowance, dated Dec. 11, 2019, from corresponding U.S. Appl. No. 16/278,122.
Notice of Allowance, dated Dec. 11, 2019, from corresponding U.S. Appl. No. 16/593,634.
Notice of Allowance, dated Dec. 12, 2017, from corresponding U.S. Appl. No. 15/169,643.
Notice of Allowance, dated Dec. 12, 2017, from corresponding U.S. Appl. No. 15/619,212.
Notice of Allowance, dated Dec. 12, 2017, from corresponding U.S. Appl. No. 15/619,382.
Notice of Allowance, dated Dec. 13, 2019, from corresponding U.S. Appl. No. 16/512,033.
Notice of Allowance, dated Dec. 13, 2021, from corresponding U.S. Appl. No. 16/908,081.
Notice of Allowance, dated Dec. 13, 2021, from corresponding U.S. Appl. No. 17/347,853.
Notice of Allowance, dated Dec. 15, 2020, from corresponding U.S. Appl. No. 16/989,086.
Notice of Allowance, dated Dec. 16, 2019, from corresponding U.S. Appl. No. 16/505,461.
Notice of Allowance, dated Dec. 17, 2020, from corresponding U.S. Appl. No. 17/034,772.
Notice of Allowance, dated Dec. 18, 2019, from corresponding U.S. Appl. No. 16/659,437.
Notice of Allowance, dated Dec. 2, 2021, from corresponding U.S. Appl. No. 16/901,654.
Notice of Allowance, dated Sep. 18, 2018, from corresponding U.S. Appl. No. 16/041,545.
Notice of Allowance, dated Sep. 18, 2020, from corresponding U.S. Appl. No. 16/812,795.
Notice of Allowance, dated Sep. 2, 2022, from corresponding U.S. Appl. No. 17/380,485.
Notice of Allowance, dated Sep. 23, 2020, from corresponding U.S. Appl. No. 16/811,793.
Notice of Allowance, dated Sep. 23, 2021, from corresponding U.S. Appl. No. 17/068,454.
Notice of Allowance, dated Sep. 24, 2021, from corresponding U.S. Appl. No. 17/334,939.
Notice of Allowance, dated Sep. 25, 2020, from corresponding U.S. Appl. No. 16/983,536.
Notice of Allowance, dated Sep. 27, 2017, from corresponding U.S. Appl. No. 15/626,052.
Notice of Allowance, dated Sep. 27, 2021, from corresponding U.S. Appl. No. 17/222,523.
Notice of Allowance, dated Sep. 28, 2018, from corresponding U.S. Appl. No. 16/041,520.
Notice of Allowance, dated Sep. 29, 2021, from corresponding U.S. Appl. No. 17/316,179.
Notice of Allowance, dated Sep. 4, 2018, from corresponding U.S. Appl. No. 15/883,041.
Notice of Allowance, dated Sep. 4, 2020, from corresponding U.S. Appl. No. 16/808,500.
Notice of Allowance, dated Sep. 4, 2020, from corresponding U.S. Appl. No. 16/901,662.
Notice of Allowance, dated Sep. 9, 2021, from corresponding U.S. Appl. No. 17/334,909.
Invitation to Pay Additional Search Fees, dated Aug. 10, 2017, from corresponding International Application No. PCT/US2017/036912.
Invitation to Pay Additional Search Fees, dated Aug. 10, 2017, from corresponding International Application No. PCT/US2017/036917.
Invitation to Pay Additional Search Fees, dated Aug. 24, 2017, from corresponding Intemational Application No. PCT/US2017/036888.
Invitation to Pay Additional Search Fees, dated Jan. 18, 2019, from corresponding Intemational Application No. PCT/US2018/055736.
Invitation to Pay Additional Search Fees, dated Jan. 7, 2019, from corresponding International Application No. PCT/US2018/055773.
Invitation to Pay Additional Search Fees, dated Jan. 8, 2019, from corresponding International Application No. PCT/US2018/055774.
Invitation to Pay Additional Search Fees, dated Oct. 23, 2018, from corresponding International Application No. PCT/US2018/045296.
Agrawal et al, “Securing Electronic Health Records Without Impeding the Flow of Information,” International Journal of Medical Informatics 76, 2007, pp. 471-479 (Year: 2007).
Avepoint, Installing and Configuring the APIA System, International Association of Privacy Professionals, AvePoint, Inc.
Bang et al, “Building an Effective and Efficient Continuous Web Application Security Program,” 2016 International Conference on Cyber Security Situational Awareness, Data Analytics and Assessment (CyberSA), London, 2016, pp. 1-4 (Year: 2016).
Binns, et al, “Data Havens, or Privacy Sans Frontières? A Study of International Personal Data Transfers,” ACM, pp. 273-274 (Year: 2002).
Czeskis et al, “Lightweight Server Support for Browser-based CSRF Protection,” Proceedings of the 22nd International Conference on World Wide Web, 2013, pp. 273-284 (Year: 2013).
Falahrastegar, Marjan, et al, Tracking Personal Identifiers Across the Web, Medical Image Computing and Computer-Assisted Intervention—Miccai 2015, 18th International Conference, Oct. 5, 2015, Munich, Germany.
Friedman et al, “Informed Consent in the Mozilla Browser. Implementing Value-Sensitive Design,” Proceedings of the 35th Annual Hawaii International Conference on System Sciences, 2002, IEEE, pp. 1-10 (Year: 2002).
Ghiglieri, Marco et al; Personal DLP for Facebook, 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (Percom Workshops); IEEE; Mar. 24, 2014; pp. 629-634.
Gilda, et al, “Blockchain for Student Data Privacy and Consent,” 2018 International Conference on Computer Communication and Informatics, Jan. 4-6, 2018, IEEE, pp. 1-5 (Year. 2018).
Halevy, et al, “Schema Mediation in Peer Data Management Systems,” IEEE, Proceedings of the 19th International Conference on Data Engineering, 2003, pp. 505-516 (Year: 2003).
IAPP, Daily Dashboard, PIA Tool Stocked With New Templates for DPI, Infosec, International Association of Privacy Professionals, Apr. 22, 2014.
IAPP, ISO/IEC 27001 Information Security Management Template, Resource Center, International Association of Privacy Professionals.
International Search Report, dated Apr. 12, 2022, from corresponding International Application No. PCT/US2022/016735.
International Search Report, dated Aug. 15, 2017, from corresponding International Application No. PCT/US2017/036919.
International Search Report, dated Aug. 21, 2017, from corresponding International Application No. PCT/US2017/036914.
International Search Report, dated Aug. 29, 2017, from corresponding International Application No. PCT/US2017/036898.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036889.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036890.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036893.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036901.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036913.
International Search Report, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036920.
International Search Report, dated Dec. 14, 2018, from corresponding International Application No. PCT/US2018/045296.
International Search Report, dated Dec. 22, 2021, from corresponding International Application No. PCT/US2021/051217.
International Search Report, dated Feb. 11, 2022, from corresponding International Application No. PCT/US2021/053518.
International Search Report, dated Feb. 14, 2022, from corresponding International Application No. PCT/US2021/058274.
International Search Report, dated Jan. 14, 2019, from corresponding International Application No. PCT/US2018/046949.
International Search Report, dated Jan. 5, 2022, from corresponding Intemational Application No. PCT/US2021/050497.
Notice of Allowance, dated May 26, 2021, from corresponding U.S. Appl. No. 16/865,874.
Notice of Allowance, dated May 26, 2021, from corresponding U.S. Appl. No. 17/199,514.
Notice of Allowance, dated May 27, 2020, from corresponding U.S. Appl. No. 16/820,208.
Notice of Allowance, dated May 27, 2021, from corresponding U.S. Appl. No. 16/927,658.
Notice of Allowance, dated May 27, 2021, from corresponding U.S. Appl. No. 17/198,757.
Notice of Allowance, dated May 27, 2022, from corresponding U.S. Appl. No. 17/543,546.
Notice of Allowance, dated May 28, 2019, from corresponding U.S. Appl. No. 16/277,568.
Notice of Allowance, dated May 28, 2020, from corresponding U.S. Appl. No. 16/799,279.
Notice of Allowance, dated May 28, 2021, from corresponding U.S. Appl. No. 16/862,944.
Notice of Allowance, dated May 31, 2022, from corresponding U.S. Appl. No. 17/679,715.
Notice of Allowance, dated May 5, 2017, from corresponding U.S. Appl. No. 15/254,901.
Notice of Allowance, dated May 5, 2020, from corresponding U.S. Appl. No. 16/563,754.
Notice of Allowance, dated May 6, 2022, from corresponding U.S. Appl. No. 17/666,886.
Notice of Allowance, dated May 7, 2020, from corresponding U.S. Appl. No. 16/505,426.
Notice of Allowance, dated May 7, 2021, from corresponding U.S. Appl. No. 17/194,662.
Notice of Allowance, dated Nov. 14, 2019, from corresponding U.S. Appl. No. 16/436,616.
Notice of Allowance, dated Nov. 16, 2021, from corresponding U.S. Appl. No. 17/491,871.
Notice of Allowance, dated Nov. 2, 2018, from corresponding U.S. Appl. No. 16/054,762.
Notice of Allowance, dated Nov. 22, 2021, from corresponding U.S. Appl. No. 17/383,889.
Notice of Allowance, dated Nov. 23, 2020, from corresponding U.S. Appl. No. 16/791,589.
Notice of Allowance, dated Nov. 24, 2020, from corresponding U.S. Appl. No. 17/027,019.
Notice of Allowance, dated Nov. 25, 2020, from corresponding U.S. Appl. No. 17/019,771.
Notice of Allowance, dated Nov. 26, 2019, from corresponding U.S. Appl. No. 16/563,735.
Notice of Allowance, dated Nov. 27, 2019, from corresponding U.S. Appl. No. 16/570,712.
Notice of Allowance, dated Nov. 27, 2019, from corresponding U.S. Appl. No. 16/577,634.
Notice of Allowance, dated Nov. 3, 2020, from corresponding U.S. Appl. No. 16/719,071.
Notice of Allowance, dated Nov. 5, 2019, from corresponding U.S. Appl. No. 16/560,965.
Notice of Allowance, dated Nov. 7, 2017, from corresponding U.S. Appl. No. 15/671,073.
Notice of Allowance, dated Nov. 8, 2018, from corresponding U.S. Appl. No. 16/042,642.
Notice of Allowance, dated Nov. 9, 2020, from corresponding U.S. Appl. No. 16/595,342.
Notice of Allowance, dated Oct. 1, 2021, from corresponding U.S. Appl. No. 17/340,395.
Notice of Allowance, dated Oct. 10, 2019, from corresponding U.S. Appl. No. 16/277,539.
Notice of Allowance, dated Oct. 17, 2018, from corresponding U.S. Appl. No. 15/896,790.
Notice of Allowance, dated Oct. 17, 2018, from corresponding U.S. Appl. No. 16/054,672.
Notice of Allowance, dated Oct. 17, 2019, from corresponding U.S. Appl. No. 16/563,741.
Notice of Allowance, dated Oct. 21, 2019, from corresponding U.S. Appl. No. 16/404,405.
Notice of Allowance, dated Oct. 21, 2020, from corresponding U.S. Appl. No. 16/834,812.
Notice of Allowance, dated Oct. 22, 2021, from corresponding U.S. Appl. No. 17/346,847.
Notice of Allowance, dated Oct. 3, 2019, from corresponding U.S. Appl. No. 16/511,700.
Notice of Allowance, dated Sep. 1, 2021, from corresponding U.S. Appl. No. 17/196,570.
Notice of Allowance, dated Sep. 1, 2021, from corresponding U.S. Appl. No. 17/222,556.
Notice of Allowance, dated Sep. 1, 2022, from corresponding U.S. Appl. No. 17/480,377.
Notice of Allowance, dated Sep. 12, 2019, from corresponding U.S. Appl. No. 16/512,011.
Notice of Allowance, dated Sep. 12, 2022, from corresponding U.S. Appl. No. 17/674,187.
Notice of Allowance, dated Sep. 13, 2018, from corresponding U.S. Appl. No. 15/894,809.
Notice of Allowance, dated Sep. 13, 2018, from corresponding U.S. Appl. No. 15/894,890.
Notice of Allowance, dated Sep. 14, 2021, from corresponding U.S. Appl. No. 16/808,497.
Notice of Allowance, dated Sep. 16, 2020, from corresponding U.S. Appl. No. 16/915,097.
Notice of Allowance, dated Sep. 17, 2020, from corresponding U.S. Appl. No. 16/863,226.
Notice of Allowance, dated Sep. 18, 2018, from corresponding U.S. Appl. No. 15/,894,819.
International Search Report, dated Jan. 7, 2019, from corresponding International Application No. PCT/US2018/055772.
International Search Report, dated Jun. 1, 2022, from corresponding International Application No. PCT/US2022/016930.
International Search Report, dated Jun. 21, 2017, from corresponding International Application No. PCT/US2017/025600.
International Search Report, dated Jun. 22, 2022, from corresponding International Application No. PCT/US2022/019358.
International Search Report, dated Jun. 24, 2022, from corresponding International Application No. PCT/US2022/019882.
International Search Report, dated Jun. 6, 2017, from corresponding International Application No. PCT/US2017/025605.
International Search Report, dated Jun. 6, 2017, from corresponding International Application No. PCT/US2017/025611.
International Search Report, dated Mar. 14, 2019, from corresponding International Application No. PCT/US2018/055736.
International Search Report, dated Mar. 18, 2022, from corresponding International Application No. PCT/US2022/013733.
International Search Report, dated Mar. 4, 2019, from corresponding Intemational Application No. PCT/US2018/055773.
International Search Report, dated Mar. 4, 2019, from corresponding International Application No. PCT/US2018/055774.
International Search Report, dated May 12, 2022, from corresponding International Application No. PCT/US2022/015929.
International Search Report, dated May 17, 2022, from corresponding International Application No. PCT/US2022/015241.
International Search Report, dated May 19, 2022, from corresponding International Application No. PCT/US2022/015637.
International Search Report, dated Nov. 12, 2021, from corresponding International Application No. PCT/US2021/043481.
International Search Report, dated Nov. 19, 2018, from corresponding International Application No. PCTUS2018/046939.
International Search Report, dated Nov. 3, 2021, from corresponding International Application No. PCT/US2021/040893.
International Search Report, dated Nov. 3, 2021, from corresponding International Application No. PCT/US2021/044910.
International Search Report, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043975.
International Search Report, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043976.
International Search Report, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/043977.
International Search Report, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/044026.
International Search Report, dated Oct. 11, 2018, from corresponding International Application No. PCT/US2018/045240.
International Search Report, dated Oct. 12, 2017, from corresponding International Application No. PCT/US2017/036888.
International Search Report, dated Oct. 12, 2018, from corresponding International Application No. PCT/US2018/044046.
International Search Report, dated Oct. 16, 2018, from corresponding International Application No. PCT/US2018/045243.
International Search Report, dated Oct. 18, 2018, from corresponding International Application No. PCT/US2018/045249.
International Search Report, dated Oct. 20, 2017, from corresponding International Application No. PCT/US2017/036917.
International Search Report, dated Oct. 3, 2017, from corresponding International Application No. PCT/US2017/036912.
International Search Report, dated Sep. 1, 2017, from corresponding International Application No. PCT/US2017/036896.
International Search Report, dated Sep. 12, 2018, from corresponding International Application No. PCT/US2018/037504.
International Search Report, dated Sep. 15, 2021, from corresponding International Application No. PCT/US2021/033631.
Lebeau, Franck, et al, “Model-Based Vulnerability Testing for Web Applications,” 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation Workshops, pp. 445-452, IEEE, 2013 (Year: 2013).
Liu, Yandong, et al, “Finding the Right Consumer: Optimizing for Conversion in Display Advertising Campaigns,” Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, Feb. 2, 2012, pp. 473-428 (Year. 2012).
Lizar et al, “Usable Consents: Tracking and Managing Use of Personal Data with a Consent Transaction Receipt,” Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, 2014, pp. 647-652 (Year: 2014).
Ma Ziang, et al, “LibRadar: Fast and Accurate Detection of Third-Party Libraries in Android Apps,” 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering Companion (ICSE-C), ACM, May 14, 2016, pp. 653-656, DOI: http://dx.doi.org/10.1145/2889160.2889178, p. 653, r.col, par. 1-3; figure 3 (Year: 2016).
Mandal, et al, “Automated Age Prediction Using Wrinkles Features of Facial Images and Neural Network,” International Journal of Emerging Engineering Research and Technology, vol. 5, Issue 2, Feb. 2017, pp. 12-20 (Year: 2017).
Moiso et al, “Towards a User-Centric Personal Data Ecosystem The Role of the Bank of Individual's Data, ” 2012 16th International Conference on Intelligence in Next Generation Networks, Berlin, 2012, pp. 202-209 (Year: 2012).
Pfeifle, Sam, The Privacy Advisor, IAPP and AvePoint Launch New Free PIA Tool, International Association of Privacy Professionals, Mar. 5, 2014.
Pfeifle, Sam, The Privacy Advisor, IAPP Heads to Singapore with APIA Template in Tow, International Association of Privacy Professionals, https://iapp.org/news/a/iapp-heads-to-singapore-with-apia-template_in_tow/, Mar. 28, 2014, p. 1-3.
Qing Jiang et al, “The (P, a, K) Anonymity Model for Privacy Protection of Personal Information in the Social Networks,” 2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference, vol. 2 IEEE, 2011, pp. 420-423 (Year. 2011).
Srivastava, Agrima, et al, Measuring Privacy Leaks in Online Social Networks, International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013.
Tanwar, et al, “Live Forensics Analysis: Violations of Business Security Policy,” 2014 International Conference on Contemporary Computing and Informatics (IC31), 2014, pp. 971-976 (Year: 2014).
Thuraisingham, “Security Issues for the Semantic Web,” Proceedings 27th Annual International Computer Software and Applications Conference, COMPSAC 2003, Dallas, TX, USA, 2003, pp. 633-638 (Year. 2003).
Written Opinion of the International Searching Authority, dated Jun. 6, 2017, from corresponding International Application No. PCT/US2017/025611.
Written Opinion of the International Searching Authority, dated Apr. 12, 2022, from corresponding International Application No. PCT/US2022/016735.
Written Opinion of the International Searching Authority, dated Aug. 15, 2017, from corresponding International Application No. PCT/US2017/036919.
Written Opinion of the International Searching Authority, dated Aug. 21, 2017, from corresponding International Application No. PCT/US2017/036914.
Written Opinion of the International Searching Authority, dated Aug. 29, 2017, from corresponding International Application No. PCT/US2017/036898.
Written Opinion of the International Searching Authority, dated Aug. 8, 2017, from corresponding International Application No. PCT/US2017/036889.
Alkalha et al, “Investigating the Effects of Human Resource Policies on Organizational Performance: An Empirical Study on Commercial Banks Operating in Jordan,” European Journal of Economics, Finance and Administrative Science, pp. 1-22 (Year: 2012).
Aman et al, “Detecting Data Tampering Attacks in Synchrophasor Networks using Time Hopping,” IEEE, pp. 1-6 (Year: 2016).
Amar et al, “Privacy-Aware Infrastructure for Managing Personal Data, ” ACM, pp. 571-572, Aug. 22-26, 2016 (Year: 2016).
Antunes et al, “Preserving Digital Data in Heterogeneous Environments”, ACM, pp. 345-348, 2009 (Year: 2009).
Ardagna, et al, “A Privacy-Aware Access Control System,” Journal of Computer Security, 16:4, pp. 369-397 (Year: 2008).
Avepoint, Automating Privacy Impact Assessments, AvePoint, Inc.
Avepoint, AvePoint Privacy Impact Assessment 1: User Guide, Cumulative Update 2, Revision E, Feb. 2015, AvePoint, Inc.
Ball, et al, “Aspects of the Computer-Based Patient Record,” Computers in Healthcare, Springer-Verlag New York Inc., pp. 1-23 (Year: 1992).
Banerjee et al, “Link Before You Share: Managing Privacy Policies through Blockchain,” IEEE, pp. 4438-4447 (Year: 2017).
Bansal et al, “Integrating Big Data: A Semantic Extract-Transform-Load Framework,” IEEE, pp. 42-50 (Year. 2015).
Bao et al, “Performance Modeling and Workflow Scheduling of Microservice-Based Applications in Clouds,” IEEE Transactions on Parallel and Distributed Systems, vol. 30, No. 9, Sep. 2019, pp. 2101-2116 (Year: 2019).
Barker, “Personalizing Access Control by Generalizing Access Control,” ACM, pp. 149-158 (Year: 2010).
Barr, “Amazon Rekognition Update—Estimated Age Range for Faces,” AWS News Blog, Feb. 10, 2017, pp. 1-5 (Year: 2017).
Bayardo et al, “Technological Solutions for Protecting Privacy,” Computer 36.9 (2003), pp. 115-118, (Year: 2003).
Berezovskiy et al, “A framework for dynamic data source identification and orchestration on the Web”, ACM, pp. 1-8 (Year: 2010).
Bertino et al, “On Specifying Security Policies for Web Documents with an XML-based Language,” ACM, pp. 57-65 (Year: 2001).
Bertino et al, “Towards Mechanisms for Detection and Prevention of Data Exfiltration by Insiders,” Mar. 22, 2011, ACM, pp. 10-19 (Year: 2011).
Bhargav-Spantzel et al., Receipt Management—Transaction History based Trust Establishment, 2007, ACM, p. 82-91.
Bhuvaneswaran et al, “Redundant Parallel Data Transfer Schemes for the Grid Environment”, ACM, pp. 18 (Year. 2006).
Bieker, et al, “Privacy-Preserving Authentication Solutions—Best Practices for Implementation and EU Regulatory Perspectives,” Oct. 29, 2014, IEEE, pp. 1-10 (Year: 2014).
Bin, et al, “Research on Data Mining Models for the Internet of Things,” IEEE, pp. 1-6 (Year: 2010).
Bindschaedler et al, “Privacy Through Fake Yet Semantically Real Traces,” ARXIV.ORG, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, May 27, 2015 (Year: 2015).
Bjorn Greif, “Cookie Pop-up Blocker: Cliqz Automatically Denies Consent Requests,” Cliqz.com, pp. 1-9, Aug. 11, 2019 (Year: 2019).
Borgida, “Description Logics in Data Management,” IEEE Transactions on Knowledge and Data Engineering, vol. 7, No. 5, Oct. 1995, pp. 671-682 (Year: 1995).
Brandt et al, “Efficient Metadata Management in Large Distributed Storage Systems,” IEEE, pp. 1-9 (Year. 2003).
Bujlow et al, “Web Tracking: Mechanisms, Implications, and Defenses,” Proceedings of the IEEE, Aug. 1, 2017, vol. 5, No. 8, pp. 1476-1510 (Year: 2017).
Byun, Ji-Won, Elisa Bertino, and Ninghui Li. “Purpose based access control of complex data for privacy protection.” Proceedings of the tenth ACM symposium on Access control models and technologies. ACM, 2005. (Year: 2005).
Carminati et al, “Enforcing Access Control Over Data Streams,” ACM, pp. 21-30 (Year: 2007).
Carpineto et al, “Automatic Assessment of Website Compliance to the European Cookie Law with CoolCheck,” Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society, 2016, pp. 135-138 (Year: 2016).
Castro et al, “Creating Lightweight Ontologies for Dataset Description,” IEEE, pp. 1-4 (Year. 2014).
Cerpzone, “How to Access Data on Data Archival Storage and Recovery System”, https://www.saj.usace.army.mil/Portals/44/docs/Environmental/Lake%200%20Watershed/15February2017/How%20To%20Access%20Model%20Data%20on%20DASR.pdf?ver=2017-02-16-095535-633, Feb. 16, 2017.
Cha et al, “A Data-Driven Security Risk Assessment Scheme for Personal Data Protection,” IEEE, pp. 50510-50517 (Year: 2018).
Cha, et al, “Process-Oriented Approach for Validating Asset Value for Evaluating Information Security Risk,” IEEE, Aug. 31, 2009, pp. 379-385 (Year: 2009).
Chang et al, “A Ranking Approach for Human Age Estimation Based on Face Images,” IEEE, 2010, pp. 3396-3399 (Year: 2010).
Chapados et al, “Scoring Models for Insurance Risk Sharing Pool Optimization,” 2008, IEEE, pp. 97-105 (Year: (2008).
Cheng, Raymond, et al, “Radiatus: A Shared-Nothing Server-Side Web Architecture,” Proceedings of the Seventh ACM Symposium on Cloud Computing, Oct. 5, 2016, pp. 237-250 (Year: 2016).
Choi et al, “A Survey on Ontology Mapping,” ACM, pp. 34-41 (Year. 2006).
Choi et al, “Retrieval Effectiveness of Table of Contents and Subject Headings,” ACM, pp. 103-104 (Year: 2007).
Chowdhury et al, “A System Architecture for Subject-Centric Data Sharing”, ACM, pp. 1-10 (Year: 2018).
Chowdhury et al, “Managing Data Transfers in Computer Clusters with Orchestra,” ACM, pp. 98-109 (Year. 2011).
Civili et al, “Mastro Studio: Managing Ontology-Based Data Access Applications,” ACM, pp. 1314-1317, Aug. 26-30, 2013 (Year: 2013).
Cruz et al, “Interactive User Feedback in Ontology Matching Using Signature Vectors,” IEEE, pp. 1321-1324 (Year: 2012).
Cudre-Mauroux, “ESWC 2008 Ph.D. Symposium,” The ESWC 2008 Ph.D. Symposium is sponsored by the Okkam project (http://fp7.okkam.org/), MIT, pp. 1-92 (Year: 2008).
Cui et al, “Domain Ontology Management Environment,” IEEE, pp. 1-9 (Year. 2000).
Decision Regarding Institution of Post-Grant Review in Case PGR2018-00056 for U.S. Pat. No. 9,691,090 B1, Oct. 11, 2018.
Degeling et al, “We Value Your Privacy. . . Now Take Some Cookies: Measuring the GDPRs Impact on Web Privacy,” ARXIV.ORG, Cornell University Library, 201 Olin Library Comell University, Ithaca, NY 14853, Aug. 15, 2018, pp. 1-15 (Year: 2019).
Dimou et al, “Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval”, ACM, pp. 145-152 (Year: 2015).
Dokholyan et al, “Regulatory and Ethical Considerations for Linking Clinical and Administrative Databases,” American Heart Journal 157.6 (2009), pp. 971-982 (Year: 2009).
Dowling, “Auditing Global HR Compliance,” published May 23, 2014, retrieved from https://www.shrm.org/resourcesandtools/hr-topics/ global-hr/pages/auditing-global-hr-compliance.aspx Jul. 2, 2022 (Year: 2014).
Dunkel et al, “Data Organization and Access for Efficient Data Mining”, IEEE, pp. 522-529 (Year: 1999).
Notice of Allowance, dated Dec. 23, 2019, from corresponding U.S. Appl. No. 16/656,835.
Notice of Allowance, dated Dec. 23, 2020, from corresponding U.S. Appl. No. 17/068,557.
Notice of Allowance, dated Dec. 3, 2019, from corresponding U.S. Appl. No. 16/563,749.
Notice of Allowance, dated Dec. 30, 2021, from corresponding U.S. Appl. No. 16/938,520.
Notice of Allowance, dated Dec. 31, 2018, from corresponding U.S. Appl. No. 16/159,634.
Notice of Allowance, dated Dec. 31, 2019, from corresponding U.S. Appl. No. 16/404,399.
Notice of Allowance, dated Dec. 4, 2019, from corresponding U.S. Appl. No. 16/594,670.
Notice of Allowance, dated Dec. 5, 2017, from corresponding U.S. Appl. No. 15/633,703.
Notice of Allowance, dated Dec. 6, 2017, from corresponding U.S. Appl. No. 15/619,451.
Notice of Allowance, dated Dec. 6, 2017, from corresponding U.S. Appl. No. 15/619,459.
Notice of Allowance, dated Dec. 7, 2020, from corresponding U.S. Appl. No. 16/817,136.
Notice of Allowance, dated Dec. 8, 2021, from corresponding U.S. Appl. No. 17/397,472.
Notice of Allowance, dated Dec. 9, 2019, from corresponding U.S. Appl. No. 16/565,261.
Notice of Allowance, dated Dec. 9, 2020, from corresponding U.S. Appl. No. 16/404,491.
Notice of Allowance, dated Feb. 1, 2022, from corresponding U.S. Appl. No. 17/346,509.
Notice of Allowance, dated Feb. 10, 2020, from corresponding U.S. Appl. No. 16/552,765.
Notice of Allowance, dated Feb. 11, 2021, from corresponding U.S. Appl. No. 17/086,732.
Notice of Allowance, dated Feb. 12, 2020, from corresponding U.S. Appl. No. 16/572,182.
Notice of Allowance, dated Feb. 13, 2019, from corresponding U.S. Appl. No. 16/041,563.
Notice of Allowance, dated Feb. 14, 2019, from corresponding U.S. Appl. No. 16/226,272.
Notice of Allowance, dated Feb. 14, 2022, from corresponding U.S. Appl. No. 16/623,157.
Notice of Allowance, dated Feb. 19, 2019, from corresponding U.S. Appl. No. 16/159,632.
Notice of Allowance, dated Feb. 19, 2021, from corresponding U.S. Appl. No. 16/832,451.
Notice of Allowance, dated Feb. 22, 2022, from corresponding U.S. Appl. No. 17/535,065.
Notice of Allowance, dated Feb. 24, 2021, from corresponding U.S. Appl. No. 17/034,355.
Notice of Allowance, dated Feb. 24, 2021, from corresponding U.S. Appl. No. 17/068,198.
Notice of Allowance, dated Feb. 24, 2021, from corresponding U.S. Appl. No. 17/101,106.
Notice of Allowance, dated Feb. 24, 2021, from corresponding U.S. Appl. No. 17/101,253.
Notice of Allowance, dated Feb. 24, 2022, from corresponding U.S. Appl. No. 17/234,205.
Notice of Allowance, dated Feb. 24, 2022, from corresponding U.S. Appl. No. 17/549,170.
Notice of Allowance, dated Feb. 25, 2020, from corresponding U.S. Appl. No. 16/714,355.
Notice of Allowance, dated Feb. 25, 2021, from corresponding U.S. Appl. No. 17/106,469.
Notice of Allowance, dated Feb. 26, 2021, from corresponding U.S. Appl. No. 17/139,650.
Notice of Allowance, dated Feb. 27, 2019, from corresponding U.S. Appl. No. 16/041,468.
Notice of Allowance, dated Feb. 27, 2019, from corresponding U.S. Appl. No. 16/226,290.
Notice of Allowance, dated Feb. 3, 2021, from corresponding U.S. Appl. No. 16/827,039.
Notice of Allowance, dated Feb. 3, 2021, from corresponding U.S. Appl. No. 17/068,558.
Notice of Allowance, dated Feb. 4, 2022, from corresponding U.S. Appl. No. 17/520,272.
Notice of Allowance, dated Feb. 8, 2022, from corresponding U.S. Appl. No. 17/342,153.
Notice of Allowance, dated Jan. 1, 2021, from corresponding U.S. Appl. No. 17/026,727.
Notice of Allowance, dated Jan. 11, 2022, from corresponding U.S. Appl. No. 17/371,350.
Notice of Allowance, dated Jan. 12, 2022, from corresponding U.S. Appl. No. 17/334,948.
Notice of Allowance, dated Jan. 12, 2022, from corresponding U.S. Appl. No. 17/463,775.
Notice of Allowance, dated Jan. 14, 2020, from corresponding U.S. Appl. No. 16/277,715.
Notice of Allowance, dated Jan. 15, 2021, from corresponding U.S. Appl. No. 17/030,714.
Notice of Allowance, dated Jan. 18, 2018, from corresponding U.S. Appl. No. 15/619,478.
Notice of Allowance, dated Jan. 18, 2019 from corresponding U.S. Appl. No. 16/159,635.
Notice of Allowance, dated Jan. 2, 2020, from corresponding U.S. Appl. No. 16/410,296.
Notice of Allowance, dated Jan. 23, 2018, from corresponding U.S. Appl. No. 15/619,251.
Notice of Allowance, dated Jan. 24, 2022, from corresponding U.S. Appl. No. 17/340,699.
Final Office Action, dated Nov. 8, 2022, from corresponding U.S. Appl. No. 17/151,334.
Notice of Allowance, dated Oct. 25, 2022, from corresponding U.S. Appl. No. 17/711,331.
Office Action, dated Nov. 10, 2022, from corresponding U.S. Appl. No. 17/670,341.
Office Action, dated Nov. 18, 2022, from corresponding U.S. Appl. No. 17/836,454.
Office Action, dated Nov. 29, 2022, from corresponding U.S. Appl. No. 17/838,939.
Office Action, dated Oct. 25, 2022, from corresponding U.S. Appl. No. 17/836,865.
Restriction Requirement, dated Nov. 14, 2022, from corresponding U.S. Appl. No. 17/836,872.
Zhang et al, “Data Transfer Performance Issues for a Web Services Interface to Synchrotron Experiments”, ACM, pp. 59-65 (Year: 2007).
Zhang et al, “Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data”, ACM, pp. 1425-1434 (Year. 2015).
Zheng, et al, “Methodologies for Cross-Domain Data Fusion: An Overview,” IEEE, pp. 16-34 (Year: 2015).
Zheng, et al, “Toward Assured Data Deletion in Cloud Storage,” IEEE, vol. 34, No. 3, pp. 101-107 May/Jun. 2020 (Year: 2020).
Zhu, et al, “Dynamic Data Integration Using Web Services,” IEEE, pp. 1-8 (Year. 2004).
Notice of Allowance, dated Jun. 29, 2022, from corresponding U.S. Appl. No. 17/675,118.
Notice of Allowance, dated Jun. 4, 2019, from corresponding U.S. Appl. No. 16/159,566.
Notice of Allowance, dated Jun. 5, 2019, from corresponding U.S. Appl. No. 16/220,899.
Notice of Allowance, dated Jun. 5, 2019, from corresponding U.S. Appl. No. 16/357,260.
Notice of Allowance, dated Jun. 6, 2018, from corresponding U.S. Appl. No. 15/875,570.
Notice of Allowance, dated Jun. 6, 2019, from corresponding U.S. Appl. No. 16/159,628.
Notice of Allowance, dated Jun. 7, 2021, from corresponding U.S. Appl. No. 17/099,270.
Notice of Allowance, dated Jun. 8, 2020, from corresponding U.S. Appl. No. 16/712,104.
Notice of Allowance, dated Jun. 8, 2022, from corresponding U.S. Appl. No. 17/722,551.
Notice of Allowance, dated Mar. 1, 2018, from corresponding U.S. Appl. No. 15/853,674.
Notice of Allowance, dated Mar. 1, 2019, from corresponding U.S. Appl. No. 16/059,911.
Notice of Allowance, dated Mar. 10, 2021, from corresponding U.S. Appl. No. 16/925,628.
Notice of Allowance, dated Mar. 10, 2021, from corresponding U.S. Appl. No. 17/128,666.
Notice of Allowance, dated Mar. 13, 2019, from corresponding U.S. Appl. No. 16/055,083.
Notice of Allowance, dated Mar. 14, 2019, from corresponding U.S. Appl. No. 16/055,944.
Notice of Allowance, dated Mar. 16, 2020, from corresponding U.S. Appl. No. 16/778,704.
Notice of Allowance, dated Mar. 16, 2021, from corresponding U.S. Appl. No. 17/149,380.
Notice of Allowance, dated Mar. 16, 2022, from corresponding U.S. Appl. No. 17/486,350.
Notice of Allowance, dated Mar. 17, 2020, from corresponding U.S. Appl. No. 16/560,885.
Notice of Allowance, dated Mar. 18, 2020, from corresponding U.S. Appl. No. 16/560,963.
Notice of Allowance, dated Mar. 19, 2021, from corresponding U.S. Appl. No. 17/013,757.
Notice of Allowance, dated Mar. 2, 2018, from corresponding U.S. Appl. No. 15/858,802.
Notice of Allowance, dated Mar. 2, 2022, from corresponding U.S. Appl. No. 16/872,130.
Notice of Allowance, dated Mar. 2, 2022, from corresponding U.S. Appl. No. 17/535,098.
Notice of Allowance, dated Mar. 21, 2022, from corresponding U.S. Appl. No. 17/366,754.
Notice of Allowance, dated Mar. 22, 2022, from corresponding U.S. Appl. No. 17/475,244.
Notice of Allowance, dated Mar. 22, 2022, from corresponding U.S. Appl. No. 17/504,102.
Notice of Allowance, dated Mar. 24, 2020, from corresponding U.S. Appl. No. 16/552,758.
Notice of Allowance, dated Mar. 25, 2019, from corresponding U.S. Appl. No. 16/054,780.
Notice of Allowance, dated Mar. 26, 2020, from corresponding U.S. Appl. No. 16/560,889.
Notice of Allowance, dated Mar. 26, 2020, from corresponding U.S. Appl. No. 16/578,712.
Notice of Allowance, dated Mar. 27, 2019, from corresponding U.S. Appl. No. 16/226,280.
Notice of Allowance, dated Mar. 28, 2022, from corresponding U.S. Appl. No. 17/499,609.
Notice of Allowance, dated Mar. 29, 2019, from corresponding U.S. Appl. No. 16/055,998.
Notice of Allowance, dated Mar. 31, 2020, from corresponding U.S. Appl. No. 16/563,744.
Notice of Allowance, dated Mar. 31, 2021, from corresponding U.S. Appl. No. 17/013,758.
Notice of Allowance, dated Mar. 31, 2021, from corresponding U.S. Appl. No. 17/162,205.
Notice of Allowance, dated Mar. 31, 2022, from corresponding U.S. Appl. No. 17/476,209.
Notice of Allowance, dated Mar. 4, 2022, from corresponding U.S. Appl. No. 17/409,999.
Notice of Allowance, dated May 1, 2020, from corresponding U.S. Appl. No. 16/586,202.
Notice of Allowance, dated May 11, 2020, from corresponding U.S. Appl. No. 16/786,196.
Notice of Allowance, dated May 11, 2022, from corresponding U.S. Appl. No. 17/395,759.
Notice of Allowance, dated May 13, 2021, from corresponding U.S. Appl. No. 17/101,915.
Notice of Allowance, dated May 18, 2022, from corresponding U.S. Appl. No. 17/670,354.
Notice of Allowance, dated May 19, 2020, from corresponding U.S. Appl. No. 16/505,430.
Notice of Allowance, dated May 19, 2020, from corresponding U.S. Appl. No. 16/808,496.
Notice of Allowance, dated May 20, 2020, from corresponding U.S. Appl. No. 16/707,762.
Notice of Allowance, dated May 21, 2018, from corresponding U.S. Appl. No. 15/896,790.
Notice of Allowance, dated May 25, 2022, from corresponding U.S. Appl. No. 16/872,031.
Notice of Allowance, dated May 26, 2021, from corresponding U.S. Appl. No. 16/808,493.
Related Publications (1)
Number Date Country
20230038573 A1 Feb 2023 US
Provisional Applications (1)
Number Date Country
63229854 Aug 2021 US