The present invention pertains generally to the field of knowledge management. More particularly, the present invention relates to a general purpose expertise engine capable of integration with other enterprise software technologies.
Many large companies face high product development expenditures due to inefficient awareness of existing expertise and sharing of that expertise and knowledge within the company. For example, a company may have several thousand employees spread over numerous of countries conducting research and development projects in different offices. Results developed during one research and development project in a company's office in Munich, for example, may be invaluable to another research and development project that is taking place in a company's office in New York. However, inefficient information management may cause the office in New York to unnecessarily spend thousands of dollars pursuing the same result already being sought by the team of co-workers in Munich.
The process of “capturing” knowledge in large organizations usually centers on a publishing model in which the burden falls on individual people to create documents about what they know. The process of creating documents is not only time consuming, but produces an unsatisfactory result, for several fundamental reasons. First, it is virtually impossible to capture the complete context and details of any project or business issue into a document. Information that is omitted may not have seemed important to the author, but it could be extremely valuable to someone else within the company. Second, there is a delay between the time at which business activities occur and the time at which a person can summarize those activities into a document, causing delays in availability of the latest development breakthroughs and/or the most current project statuses. In addition, not all of the information necessarily can be shared publicly. Due to the sensitive nature of some information, the originator of that information may wish to share it only with a certain set of people and/or under specific circumstances. This type of information rarely gets published, and an opportunity to gain further value from the information is often completely lost.
The present invention includes a method and system for knowledge management. In one embodiment, the method comprises identifying a plurality of profiles of entities, the profiles comprise a shared characteristic. The method also comprises generating an aggregate profile comprising contents of the plurality of profiles.
Other features of the present invention will be apparent from the following discussion.
The present invention is illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which:
A method and apparatus for knowledge management are described. Note that in this description, references to “one embodiment” or “an embodiment” mean that the feature being referred to is included in at least one embodiment of the present invention. Further, separate references to “one embodiment” in this description do not necessarily refer to the same embodiment; however, neither are such embodiments mutually exclusive, unless so stated and except as will be readily apparent to those skilled in the art. Thus, the present invention can include any variety of combinations and/or integrations of the embodiments described herein.
The present invention discloses a method and system for expertise management in an environment of a business entity. Knowledge profiles of entities are generated in order to automatically characterize individual people, groups or abstract sources of information.
It will be appreciated that the term “business entity” as used herein refers to a business entity, that utilizes services of the system of the present invention. The term “host application” as used herein refers to a software application that directly interacts with the system of the present invention. The term “client's system” as used herein refers to a computer system environment of the business entity. The term “user” as used herein refers to a user of a device, such as a handheld device, a personal computer, a workstation, etc., that provides the user with access to the features of the system of the present invention.
Introduction to Related Technology
One embodiment of the present invention utilizes Internet Message Access Protocol (IMAP). The IMAP is a protocol for retrieving email messages. It provides a method of accessing electronic mail or bulletin boards that are kept on a mail server allowing a client to access information as if it was stored locally. An IMAP server provides a message store for an incoming email message until users logon and download the message. Messages can be archived in folders, mailboxes can be shared, and the user may access multiple mail servers. IMAP provides integration with Multipurpose Internet Mail Extensions (MIME), which is a method utilized for transmitting non-text files via Internet email, that allows the users to read headers of the email messages without accepting the attached files or waiting for the attachments to download.
The invention utilizes Simple Mail Transfer Protocol (SMTP). SMTP is a standard mail TCP/IP protocol on the Internet that defines the message format and the message transfer agent, which stores and forwards email messages.
The present invention makes use of a servlets. Servlets can be Java applications, applets, which run on a Web server or application server and provide server-side processing, typically to access a database. A servlet is a Java-based alternative to Common Gateway Interface (CGI) scripts, interface programs, usually written in C or PERL, that enable an Internet server to run external programs to perform a specific function. A difference between servlets and CGI scripts is that a Java servlet is persistent, whereas a CGI script is not. This means that once it is started, the servlet stays in memory and can fulfill multiple requests. In contrast, a CGI script disappears once it has fulfilled a request.
The present invention also uses Java Database Connectivity (JDBC), which allows Java applications to access a database via an SQL language queries. Since Java Interpreters, i.e. Java Virtual Machines, are available for all major client platforms, JDBC allows generation of a platform independent database application.
In addition, another component of the present invention is JavaMail, which allows Java Applications to access an e-mail server. The invention also utilizes Simple Object Access Protocol (SOAP), which is a message-based protocol based on Extensible Markup Language (XML) for accessing services on the Web. Another component utilized by the inventions is .NET, a framework for web-based services and component software developed by Microsoft, Inc. of Redmond, Wash.
The invention also utilizes Application Program Interface (API). API is a language and message format used by an application program to communicate with an operating system or some other control program. APIs are implemented by writing function calls in the application program, which provide a linkage to a required subroutine for execution.
Exemplary Architecture
As a component of a host application, an expertise services platform provides a way to create, access and maintain profiles of entities, that automatically characterize individual people, groups, or abstract sources of information.
Profile Creation
In one embodiment of the invention a profile is created for every account in the client's system.
At 405 the content to be profiled is formatted as an email message by the host application. The profiling content may be included either in the body of the generated email message or as a MIME attachment attached to the generated email. At 410 a properties document containing the profiling properties associated with the entity and extracted from the entity's account is created and attached to the email message. In one embodiment the properties document is an XML document. At 415 the host application places the generated email message in a storage bin, utilizing an appropriate protocol, for example, SMTP or IMAP. In one embodiment the generated email messages may be placed in the storage bin via API routines, which are described later. In one embodiment the associated text storage bin is an IMAP storage bin. It will be appreciated that the storage bin does not have to be IMAP type and may be any type of a storage bin to store the generated email message to be processed by the expertise services platform 100.
The profiler 205, upon receiving the associated text, determines to which profile the extracted terms belong by utilizing information in the attached properties document. The profiling properties extracted from the attachment also provide the expertise services platform 100 with information such as to which term set the extracted terms belong, how heavily these terms should be weighted in the profile, etc. The profiler 205 profiles all of the text or document within the email, with the exception of the attachment used for profiling properties. Once the profiling is complete, the document may be deleted from the storage bin.
It will be appreciated that the host application may provide the associated text to the expertise services platform 100 utilizing any of a variety of other techniques well known in the art, such that the present invention is not limited to the technique described above.
Term Extraction
In one embodiment of the present invention, upon retrieving the associated text from the storage bin and placing it in the associated text storage bin 240, the profiler 205 directs the converter 215 to determine whether the format conversion is necessary.
At 510 the profiler 205 extracts terms from the associated information stored in the associated text storage bin 240. The terms are extracted in the form of, for example, grammar terms, noun phrases, word collections or single words. Upon extraction of the terms, the terms are placed in the term database 235 prior to the profiler 205 determining which terms are to be added to the entity's profile. The profiler 205 determines to which profile the terms belong by processing information in the attachment. During term extraction the profiler 205 may determine the total number of words comprising the associated text, the density of recurring words within the document, the length of each term, i.e., the number of words that constitute the term, the part of the speech that each word within the document constitutes, and a word type, e.g. whether the terms is a lexicon term specific to the business entity's environment. The profiler 205 has access to a database of lexicon terms (not shown), which may identify both universal lexicon terms and environment lexicon terms specific to an environment within which the expertise services platform is being employed. Upon extraction of the terms, the profiler 205 determines the relevance of each extracted term in order to determine whether the term is relevant and needs to be added to the entity profile, by comparing the extracted terms to the terms in the universal lexicon terms and environment lexicon terms. In one embodiment, the confidence update module 220 assigns a value to each term based on a set of predetermined thresholds, such as the number of occurrences of a term in the associated text, the length of the term, a part of speech indication, etc. Upon the confidence update module 220 assigning the value to each term, the profiler 205 determines if the value is higher than a predetermined threshold, in which case the term is added to the entity's profile. Techniques for determining the relevance of a term in a document are well known in the art and do not require any further explanation. In one embodiment upon extraction of the terms and identification of the terms matching the universal lexicon terms and/or environment lexicon terms, the profiler 205 determines the term sets to which the extracted terms belong.
A profile of the entity may comprise several term sets, for example a private term set, a public term set, a set comprising terms corresponding to a particular field of the lexicon, a fixed term set comprising terms with the highest value assigned by the confidence update module, etc. Upon retrieving information from the attachment comprising profiling information, the profiler 205 may identify the term set to which the extracted terms belong. For example, the profiling attachment may specify that the terms extracted from the associated text should be associated with the public term set. Hence, the profiler 205 places the extracted terms from the associated text into the public term set of a profile. In one embodiment a term set may comprise subsets relating to different fields of expertise. For example, the public term set may comprise a networking subset including terms relating to the network technology. Upon extracting terms from the associated text and comparing the terms to the universal lexicon terms and/or environment lexicon terms, the profiler 205 may determine the subterm sets to which the terms may belong.
Upon identification of the extracted terms to be added to the entity's profile and determination of term sets to which the extracted terms should be added, the profile transfer 210 transfers the terms from the term database 235 to the profile database 225. In one embodiment the profile transfer 210 determines whether the profile of the entity already contains all the term sets and all the subsets to which the extracted terms belong. Continuing with the example above, upon determining that the “router” term belongs to the networking subset, the profile transfer 210 determines whether the profile of the entity already contains a networking subset. If the profile already includes a networking subset, the profile transfer 210 adds the extracted term to the subset. The profile transfer 210 creates the networking subset and inserts the extracted term to the newly created subset. The host application may specify the allowed terms sets within a particular profile. For example, the host application may not authorize presence of term sets in profiles, in which case the expertise profile transfer places the terms in a “default” term set.
In one embodiment the profile database 225 comprises historical information about each profile in the expertise services platform 100, such as the list of all the terms with confidence levels for each term. Upon transferring the extracted terms to the profile database 225, the profile transfer 210 transfers the latest added terms to the search database 230 in order to provide users with the latest information about the expertise in the client's environment.
In one embodiment, at predetermined time periods the confidence update module 220 determines whether the confidence levels of any terms need to be changed and whether any terms need to be removed from the profile due to the non-usage of these terms during a predetermined time interval. The confidence module update 220, upon recalculating the confidence levels, updates the profile database 225 and invokes the profile transfer module 210 to reflect the latest changes in the search database 230.
In one embodiment of the present invention, the profiler 205 may create an aggregate profile of a group of individuals, such as a corporate department, a news group, etc. For example, the profiler 205 may generate an aggregate profile for a sales department of the business entity. The host application may direct the expertise service platform 100 to generate an aggregate profile for a particular department. Continuing with the above example, the host application may direct the expertise services platform 100 to generate the aggregate profile for the sales department. The profiler 205 accesses the profile database 225 and determines which profiles belong to entities from the sales department by examining an appropriate field of the account property information. Each individual profile that belongs to an entity from the sales department is added to the aggregate profile for the sales department. In one embodiment the aggregate profiles are of the same format as individual profiles described above; that is, the aggregate profiles have term sets comprising collection of terms of the individual profiles used to generate the aggregate profile. In one embodiment an aggregate profile is a snapshot of individual profiles representing a group of entities at a specific point in time. In another embodiment the aggregate profile comprises the most current terms sets and is updated by the profile transfer module 225 in a manner described above with respect to individual profiles. It will be appreciated that an aggregate profile may include individual profiles sharing any similar characteristics and the present invention is not limited to an exemplary characteristic presented above.
Expertise Searching
In one embodiment of the present invention, the host application provides the user, e.g., an employee of the business entity, with an interface in order for the user to specify a type of expertise that the user requires. The user may utilize keywords to specify the required expertise. The user may also provide the system with a specific question or direct the system to search by context by providing a block of text. Upon submitting a query the host application forwards the query to the expertise services platform 100. In one embodiment the query is forwarded to the expertise services platform in a manner described above, by compiling the query into an email message format and submitting it to the expertise services platform 100. Upon receiving the email message with the query, the search engine 245 extracts the terms from the query and searches the search database 230 for profiles that contain matching terms in the public subset of the profiles. In one embodiment, the search engine 245 identifies profiles that comprise matching terms in the private subsets and prompts the entities of the profiles for authorization to utilize the information in the search result generated for the received query.
In one embodiment the user are provided with a list of people who were identified as experts in the area to which the user's query related.
Expertise Services Platform API
In one embodiment of the invention the host application communicates with the expertise services platform 100 utilizing a variety of API routines 202. For example, the client's system administrator may utilize administration API routines in order to configure the properties that define how a host application may interact with the expertise services platform 100. The administration API routines may also allow registration of applications that are able to communicate with the expertise services platform 100. For example, a corporation may desire to enable several applications to interact with the expertise services platform 100, such as a workgroup collaboration application, a project management and resource allocation application, a call center ticket routing application, etc. In one embodiment the API routines 202 may provide the client with the ability to create and manage databases used by the expertise services platform 100. In addition, the client's system administrator may utilize administration API routines to manage servers that comprise expertise services platform 100 components.
In one embodiment of the invention the host application utilizes account management API routines in order to provide the expertise services platform 100 with access permissions on each profile associated with an account, to create, manage, modify and delete accounts for which profiles are created and maintained by the expertise services platform 100. The host application, in one embodiment, utilizes the account management API routines to create log in and log out methods and to create different administrator-type accounts. Account management API routines may also allow the host application to manage contact information tied to an account.
In one embodiment accounts are defined by a collection of XML terms.
In one embodiment the host application utilizes expertise profiling API routines in order to submit content to be profiled to the expertise services platform 100. In addition, the host application may utilize the profiling API routines to provide the expertise services platform 100 with the relevance weighting to be set for the terms in an incoming message.
In one embodiment of the invention, the expertise services platform 100 provides the developers of the client's system with search API routines that allow the host application to configure the expertise services platform 100 to support features such as performing a search for an expert utilizing one or more keywords or a block of text, including matching terms and their confidence levels along with the profiles of the found experts when presenting a user with search results, displaying the position of words extracted in the original query text and specifying how the terms link to the terms within the matching profiles. The search API routines may also allow the client's system developers to specify a limit on the number of experts to be included in the search results based on the strength of the match. In addition the client's system developers may specify the information to be included in search results such as name, e.g. first and last name, of an entity who was identified as an expert in the requested information field, contact information, e.g. department/organization name, job title, address, phone number, email, matched terms with strength of match, etc.
Profile management API routines allow the client's system developers to configure the expertise services platform 100 to allow account owners to retrieve one or more term sets within their profiles. The account owners may also be allowed to move terms from one term set to another. The developers of the client's system may utilize the profile management API routines to instruct the expertise services platform 100 to place particular terms into specific term sets at the time the terms are added to a profile. The profile management API routines also allow the developers of the client's system to configure the expertise services platform 100 to export the profiles in order to allow applications other than the host application to access profiles of the entity. In one embodiment the privacy levels set by the owning account are retained and terms that are located in the private term sets are not exported. In one embodiment an exported profile consists of a data structure containing all the terms and their associated attributes in the specified account profile. Attributes include the publication status, e.g., privacy level, confidence metric, etc. In one embodiment the internal metrics utilized by the expertise services platform 100 to generate confidence levels of the terms are not included in the data structure. The data structure may be an XML formatted data structure.
In one embodiment the developers of the client's system perform expertise assessment via expertise assessment API routines. For example, the developers can create aggregate profiles, consolidating a collection of individual profiles for searching, organizational evaluation or for historical tracking over time. Aggregates may be created for any logical group of entities. In one embodiment, there may be a minimum number of profiles that need to be selected in order to generate an aggregate profile. In one embodiment, the developers may invoke an API function in order to instruct the expertise services platform to perform a search on the profiles and suggest profiles to be included in an aggregate profile. For example, the developers may instruct the expertise services platform to suggest profiles to be included in the Sales Department aggregate profile. The developers may also direct the expertise services platform to suggest aggregate profiles for every department.
In one embodiment the developers of the client's system perform term clustering by accessing the term clustering API. For example, the developers can create easy-to-read “snapshots” that quickly summarize the expertise represented by a single profile or within a set of profiles, such as all profiles within the Sales department. Term clusters are created by dynamically clustering together terms that relate to a specific area of expertise. These groupings are based on the strongest words in a profile or set of profiles (a word's strength is derived from the confidence of the terms that contain it.) Terms that contain these words are then dynamically grouped together.
The reporting API routines provide developers of the client's system with ability to obtain statistical information about the expertise services platform 100. In one embodiment the expertise services platform 100 provides details of the status and permissions of specified accounts such as whether the account is active, whether there is an associated profile, etc. In one embodiment the login activity is provided to the developers of the system when a reporting API function is invoked. The login activity report may comprise a total number of accounts that have logged in and those that have not logged in during a specified time period. In one embodiment the expertise services platform 100 returns the status report for a particular account specified by the developers. The expertise services platform 100 may also provide a term summary including a number of terms contained in every term set of a specified profile with identification of a status of each term, i.e. active or inactive. In one embodiment active terms are the ones that were utilized during a predetermined time period, for example last two months. In one embodiment, the expertise services platform 100 provides statistics on terms within term sets over the entire population of the profiles within the database.
Document summary API routines provide statistics on the types of documents that have been submitted into expertise services platform 100 to form the profiles. In one embodiment the types of documents include an archive document, which is a file such as a text document, a spreadsheet or presentation submitted directly into the expertise services platform 100; an email document which is an e-mail message sent to the profiler; an email attachment document which is the document that was included as an attachment to an email; unknown document which is a document that was not recognized by the expertise services platform 100 and was not profiled; discarded document which is a document that was not profiled because the document did not meet the minimum or maximum size criteria, or the document could not be read because id did not contain text-based content or was password-protected.
The expertise services platform may also provide the developers of the client's system with information about database status when a particular API function is invoked. The information may include the size of the database and the size of every object in the database. The information may also include unique words in the database, terms stored in the profiles, email addresses extracted during profiling, total profiled documents, etc.
It will be recognized that many of the features and techniques described above may be implemented in software. Likewise, hardwired circuitry may be used in place of software, or in combination with software, to implement the features described herein. Thus, the present invention is not limited to any specific combination of hardware circuitry and software, nor to any particular source of software. Moreover, components of the invention may reside on a processing system including a processor and a storage medium, such as a personal computer server-class computer, workstation, etc. Processing systems such as this are well known in the art and do not require any further explanation. The memory can store instructions and/or data to implement the process described above.
Thus, a method and apparatus for field of knowledge management have been described. Although the present invention has been described with reference to specific exemplary embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention as set forth in the claims. Accordingly, the specification and drawings are to be regarded in an illustrative sense rather than a restrictive sense.
Number | Name | Date | Kind |
---|---|---|---|
4914586 | Swinehart et al. | Apr 1990 | A |
4970681 | Bennett | Nov 1990 | A |
5051891 | MacPhail | Sep 1991 | A |
5093918 | Heyen et al. | Mar 1992 | A |
5247575 | Sprague et al. | Sep 1993 | A |
5247661 | Hager et al. | Sep 1993 | A |
5251131 | Masand et al. | Oct 1993 | A |
5251159 | Rowson | Oct 1993 | A |
5276869 | Forrest et al. | Jan 1994 | A |
5297057 | Kramer et al. | Mar 1994 | A |
5325466 | Kornacker | Jun 1994 | A |
5331579 | Maguire, Jr. et al. | Jul 1994 | A |
5333237 | Stefanopoulos et al. | Jul 1994 | A |
5428740 | Wood et al. | Jun 1995 | A |
5428778 | Brookes | Jun 1995 | A |
5438526 | Itoh et al. | Aug 1995 | A |
5442778 | Pedersen et al. | Aug 1995 | A |
5446891 | Kaplan et al. | Aug 1995 | A |
5473732 | Chang | Dec 1995 | A |
5481741 | McKaskle et al. | Jan 1996 | A |
5483650 | Pedersen et al. | Jan 1996 | A |
5488725 | Turtle et al. | Jan 1996 | A |
5493729 | Nigawara et al. | Feb 1996 | A |
5513126 | Harkins et al. | Apr 1996 | A |
5530852 | Meske, Jr. et al. | Jun 1996 | A |
5541836 | Church et al. | Jul 1996 | A |
5544067 | Rostoker et al. | Aug 1996 | A |
5555426 | Johnson et al. | Sep 1996 | A |
5586218 | Allen | Dec 1996 | A |
5608900 | Dockter et al. | Mar 1997 | A |
5628011 | Ahamed et al. | May 1997 | A |
5659731 | Gustafson | Aug 1997 | A |
5659732 | Kirsch | Aug 1997 | A |
5664115 | Fraser | Sep 1997 | A |
5692107 | Simoudis et al. | Nov 1997 | A |
5696965 | Dedrick | Dec 1997 | A |
5704017 | Heckerman et al. | Dec 1997 | A |
5717914 | Husick et al. | Feb 1998 | A |
5717923 | Dedrick | Feb 1998 | A |
5720001 | Nguyen | Feb 1998 | A |
5724567 | Rose et al. | Mar 1998 | A |
5727129 | Barrett et al. | Mar 1998 | A |
5754938 | Herz et al. | May 1998 | A |
5754939 | Herz et al. | May 1998 | A |
5768508 | Eikeland | Jun 1998 | A |
5778364 | Nelson | Jul 1998 | A |
5794210 | Goldhaber et al. | Aug 1998 | A |
5802320 | Baehr et al. | Sep 1998 | A |
5802518 | Karaev et al. | Sep 1998 | A |
5809297 | Kroenke et al. | Sep 1998 | A |
5812434 | Nagase et al. | Sep 1998 | A |
5835087 | Herz et al. | Nov 1998 | A |
5855008 | Goldhaber et al. | Dec 1998 | A |
5867799 | Lang et al. | Feb 1999 | A |
5872850 | Klein et al. | Feb 1999 | A |
5892909 | Grasso et al. | Apr 1999 | A |
5899981 | Taylor et al. | May 1999 | A |
5907677 | Glenn et al. | May 1999 | A |
5907836 | Sumita et al. | May 1999 | A |
5913210 | Call | Jun 1999 | A |
5913212 | Sutcliffe et al. | Jun 1999 | A |
5924090 | Krellenstein | Jul 1999 | A |
5924108 | Fein et al. | Jul 1999 | A |
5931907 | Davies et al. | Aug 1999 | A |
5950200 | Sudai et al. | Sep 1999 | A |
5974412 | Hazlehurst et al. | Oct 1999 | A |
5995597 | Woltz et al. | Nov 1999 | A |
5995943 | Bull et al. | Nov 1999 | A |
5999932 | Paul | Dec 1999 | A |
5999975 | Kittaka et al. | Dec 1999 | A |
6005597 | Barrett et al. | Dec 1999 | A |
6006200 | Boies et al. | Dec 1999 | A |
6006221 | Liddy et al. | Dec 1999 | A |
6009410 | LeMole et al. | Dec 1999 | A |
6014644 | Erickson | Jan 2000 | A |
6021439 | Turek et al. | Feb 2000 | A |
6023762 | Dean et al. | Feb 2000 | A |
6026374 | Chess | Feb 2000 | A |
6029195 | Herz | Feb 2000 | A |
6038560 | Wical | Mar 2000 | A |
6044205 | Reed et al. | Mar 2000 | A |
6044376 | Kurtzman, II | Mar 2000 | A |
6049797 | Guha et al. | Apr 2000 | A |
6052122 | Sutcliffe et al. | Apr 2000 | A |
6052709 | Paul | Apr 2000 | A |
6052714 | Miike et al. | Apr 2000 | A |
6061681 | Collins | May 2000 | A |
6064980 | Jacobi et al. | May 2000 | A |
6094652 | Faisal | Jul 2000 | A |
6105023 | Callan | Aug 2000 | A |
6112186 | Bergh et al. | Aug 2000 | A |
6115709 | Gilmour et al. | Sep 2000 | A |
6119167 | Boyle | Sep 2000 | A |
6151600 | Dedrick | Nov 2000 | A |
6154783 | Gilmour et al. | Nov 2000 | A |
6161139 | Win et al. | Dec 2000 | A |
6175831 | Weinreich et al. | Jan 2001 | B1 |
6182067 | Persnell et al. | Jan 2001 | B1 |
6182131 | Dean et al. | Jan 2001 | B1 |
6195660 | Polnerow et al. | Feb 2001 | B1 |
6199077 | Inala et al. | Mar 2001 | B1 |
6205456 | Nakao | Mar 2001 | B1 |
6205472 | Gilmour | Mar 2001 | B1 |
6230189 | Sato et al. | May 2001 | B1 |
6233590 | Shaw et al. | May 2001 | B1 |
6253202 | Gilmour | Jun 2001 | B1 |
6253216 | Sutcliffe et al. | Jun 2001 | B1 |
6269369 | Robertson | Jul 2001 | B1 |
6292769 | Flanagan et al. | Sep 2001 | B1 |
6298348 | Eldering | Oct 2001 | B1 |
6327590 | Chidlovskii et al. | Dec 2001 | B1 |
6330610 | Docter et al. | Dec 2001 | B1 |
6353827 | Davies et al. | Mar 2002 | B1 |
6360227 | Aggarwal et al. | Mar 2002 | B1 |
6374237 | Reese | Apr 2002 | B1 |
6377949 | Gilmour | Apr 2002 | B1 |
6397233 | Okawa et al. | May 2002 | B1 |
6404762 | Luzeski et al. | Jun 2002 | B1 |
6405197 | Gilmour | Jun 2002 | B2 |
6405243 | Nielsen | Jun 2002 | B1 |
6415283 | Conklin | Jul 2002 | B1 |
6421669 | Gilmour et al. | Jul 2002 | B1 |
6434607 | Haverstock et al. | Aug 2002 | B1 |
6449682 | Toorians | Sep 2002 | B1 |
6460036 | Herz | Oct 2002 | B1 |
6571245 | Huang et al. | May 2003 | B2 |
6629097 | Keith | Sep 2003 | B1 |
6640229 | Gilmour et al. | Oct 2003 | B1 |
6647384 | Gilmour | Nov 2003 | B2 |
6651039 | Ikuta et al. | Nov 2003 | B1 |
6651253 | Dudkiewicz et al. | Nov 2003 | B2 |
6675299 | Porter et al. | Jan 2004 | B2 |
6711570 | Goldberg et al. | Mar 2004 | B1 |
6711585 | Copperman et al. | Mar 2004 | B1 |
6732358 | Siefert | May 2004 | B1 |
6820204 | Desai et al. | Nov 2004 | B1 |
6832224 | Gilmour | Dec 2004 | B2 |
6901394 | Chauhan et al. | May 2005 | B2 |
6970879 | Gilmour | Nov 2005 | B1 |
7203725 | Gilmour et al. | Apr 2007 | B1 |
20010013029 | Gilmour | Aug 2001 | A1 |
20010047276 | Eisenhart | Nov 2001 | A1 |
20020078050 | Gilmour | Jun 2002 | A1 |
20020165861 | Gilmour | Nov 2002 | A1 |
20020194178 | Gilmour et al. | Dec 2002 | A1 |
20050004874 | Gilmour et al. | Jan 2005 | A1 |
20070112845 | Gilmour et al. | May 2007 | A1 |
Number | Date | Country |
---|---|---|
0 751 471 | Jan 1997 | EP |
WO 9623265 | Aug 1996 | WO |
WO 9702537 | Jan 1997 | WO |
WO 9804061 | Jan 1998 | WO |
WO 9840832 | Sep 1998 | WO |
WO 9939279 | Aug 1999 | WO |
Entry |
---|
Holtz, Shel. “Intranets: What's all the excitement?” Communication World. San Francisco: Jun./Jul. 1996. vol. 13, Iss. 6; p. 54. |
Welcome to enonymous.com, Web page, “Be Privacy Aware . . . Be enonymous”, http:/ /www.enonymous.com/default.asp. |
Enonymous Web Page, “Why be enonymous?”, http:/ /www.enonymous.com/whybeenon.asp. |
Enonymous Web Page, What is enonymous advisor?, http:/ /www.enonymous.com/whatisit.asp. |
Enonymous Web Page, “How enonymous advisor beta works . . . ”, http:/ /www.enonymous.com/howitworks.asp. |
Enonymous Web Page, “The enonymous zone . . . ”, http:/ /www.enonymous.com/zone.asp. |
Enonymous Web Page, “The enonymous profile . . . ”, http:/ /www.enonymous.com/profile.asp. |
Enonymous Web Page, “Frequently Asked Questions”, http:/ /www.enonymous.com/faq.asp. |
Yenta: A Multi-Agent, Referral-Based Matchmaking System, Leonard N. Foner, The First International Conference on Autonomous Agents (Agents '97), Marina del Rey, CA, 1997. |
“A Multi-Agent Referral System for Matchmaking”, Leonard N. Foner, The First International Conference on the Practical Applications of Intelligent Agents and Multi-Agent Technology, London UK, Apr. 1006. |
“Clustering and Information Sharing in an Ecology of Cooperating Agents”, Leonard N. Foner, AAAI Workshop on Information Gathering in Distributed, Heterogenous Environments '95, Palo Alto, CA 1995. |
“Somewhat-by-topic linearization of Yenta,” Leonard Foner, last modified Feb. 11, 1997, http:/ /www.media.mit.edu/people/foner/Yenta/linearization-by-topic.html. |
“Political Artifacts and Personal Privacy: The Yenta Multi-Agent Distributed Matchmaking System”, Leonard Newton Foner, Apr. 30, 1999, © Massachusetts Institute of Technology, 1999. |
“Taking the byte out of cookies: privacy, consent, and the Web” Daniel Lin, and Michael C. Loui pp. 39-51—Proceeding of the ethics and social impact component on Shaping policy on the information age May 10-12, 1998. |
“A Security Policy Model for Clinical Information Systems”—Anderson, R. J—Security and Privacy, 1996, Proceeding IEEE Symposium, May 6-8, 1996 pp. 30-43. |
“Verity introduces new Profiler Kit and enhanced developer's Kit” IAC Newsletter Collection—M2 Presswire—Aug. 1998. |
Integrator's choice awards; Brambert, Dave; Biangi, Susan—Network VAR V5.n10 p. 28 Oct. 1997. |
“IS Puts Notes to the Test”, Datamation, Mark Schlack vol. 37, No. 15, pp. 24-26, Aug. 1, 1991. |
“MAIL-MAN”: A Knowledge-Based Mail Assistant for Managers, Journal of Organizational Computing, L.F. Motiwalla and J.F. Nunamaker, Jr., vol. 2, No. 2, pp. 131-154, 1992 (abstract only). |
“Topic Real-Time”, HP-UX-Documentation Disc 50726-10186 (from Software Patent Institute Database of Software Technologies), Feb. 1, 1995. |
“AskSam for Windows Getting Started Guide”, (from Software Patent Institute Database of Software Technologies), first section, May 30, 1995. |
“EZ Reader: Embedded AI for Automatic Electronic Mail Interpretation and Routing”, Proceedings of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference, A. Rice, J. Hsu, A. Angotti and R. Piccolo, vol. 2, pp. 1507-1517, Aug. 4-8, 1996 (INSPEC Abstract). |
“Information Management for Knowledge Amplification in Virtual Enterprises”, J. Numata et al., IEMC Proceedings, pp. 281-285, Aug. 18-20, 1996 (INSEC Abstract). |
http:/ /www.email-software.com/pages/00108.htm, review of “Emailrobot for Exchange/SMTP”. |
http:/ /www.email-software.com/pages 00033.htm, review of “Signup V2.0”. |
“Knowledge Management: Fuel for Innovation”, Bob Evans, CPM net Information Week on Line, Oct. 20, 1997. |
“Knowing What We Know”, Justin Hibbard, CPM net Information Week on Line, Oct. 20, 1997. |
“Knowledge Management Evaluation Scenario”, Jeff Angus with Jeetu Patel and Joe Fenner, CPM net Information Week on Line, Mar. 16, 1998. |
“Knowledge Management Takes Industry's Center Stage”, Elliot Maise, CMP net Computer Reseller News, Feb. 2, 1998, Issue 774. |
“Knowledge Management: Great Concept . . . But What is It?”, Jeff Angus, Jeetu Patel and Jennifer Harty, CMP net, Information Week on Line, Mar. 16, 1998. |
“Knowledge Management's Net Gain”, Kevin Jones, ZD net, Inter@ctive Week, Feb. 24, 1998. |
“Open Sesame Site Just Works”, Bill Burke, BusinessToday.com, http:/ /www.opensesame.com, Today's Column, Jan. 22, 1998. |
“New eCommerce and Entertainment Web Site Demonstrates Leading Edge Personalization and Privacy Features” (press release), http://www.opensesame.com, Jan. 20, 1998. |
“Neutral Agent Enables Personalized Surfing”, R. Colin Johnson, CMP net TechWeb, http:/ /www.techweb.com. Feb. 4. 1998. |
“Open Sesame and Verity Open Doors to Personalized Software”, KMWorld.com, http:/ /www.kmworld.com, Feb. 6, 1998. |
“Life Span vs Life Spam”, George Gilder, Forbes ASAP, http:/ /www.forbes.com/asap, Apr. 6, 1998. |
“Learn Sesame gets more personal”, Jim Rapoza, PC Week Online, http:/ /www.zdnet.com/pcweek/reviews, Mar. 18, 1998. |
“Natrificial Software Technologies Unveils Internet Brain Publishing” (press release), Natrificial Software Technologies, http:/ /www.natrificial.com, Jun. 9, 1998. |
“Natrificial Software Technologies Introduces the Brain” (press release), Natrificial Software Technologies, http:/ /www.natrificial.com Jan. 26, 1998. |
“The Brain: Much More the Way You Think”, Scot Finnie, CMP Net Windows Magazine, http:/ /www.windowsmagazine.com, May 1, 1998. |
“Your Brain on Windows”, Leslie Ayers, ZD Net Products, http:/ /www.zdnet.com/products, Apr. 1998. |
“What's New”, Natrificial Software Technologies, http:/ /www.natrificial.com, 1998. |
“Natrificial Software Technologies”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
“Always Thinking Ahead”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
“Digitize Your Mind”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
“It's Your Thought That Counts”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
“Knowledge if Power”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
“Free Your Mind”, Natrificial Software Technologies, http:/ /www.natrificial.com. |
, “Abuzz's Mission”Abuzz, http:/ /www.abuzz.com. |
“Beehive”, Abuzz, http:/ /www.abuzz.com. |
“Beehive: White Papers”, Abuzz, http:/ /www.abuzz.com/home/white—papers.htm. |
Open Sesame, http:/ /www.opensesame.com. |
Open Sesame: The Company, http:/ /www.opensesame.com/company.html. |
Open Sesame Published Papers, http:/ /www.opensesame.com/co—02.html. |
Open Sesame: Agent Sourcebook, http:/ /www.opensesame.com/co—03.html. |
Open Sesame: Products; Learn Sesame, http:/ /www.opensesame.com/products.html. |
Open Sesame: Products; Why Personalize?, http:/ /www.opensense.com/prod—01.html. |
Open Sesame: Products: Benefits, http:/ /www.opensesame.com/prod—02.html. |
Open Sesame: Products; Competitive Summary, http:/ /www.opensesame.com/prod—03.html. |
Open Sesame: Products; Product Datasheet, http:/ /www.opensesame.com/prod—04.html. |
Open Sesame: Products/Demos, http:/ /www.opensesame.com/product—05.html. |
e-Genie by Open Sesame: Your Entertainment Genie!, http:/ /egenie.opensesame.com/. |
Open Sesame: Products; eGenie Live!, http:/ /www.opensesame.com/prod—06.html. |
Open Sesame: Commitment to Privacy, http:/ /www.opensesame.com/privacy.html. |
“A Short Introduction to NPtool”, Atro Voutilainen, A Short Introduction to NPtool, http:/ /www.lingsoft.fi/doc/nptool/intro/. |
NPtool Intro: Overview, http:/ /www.lingsoft.fi/doc/nptool/intro/overview.html. |
NPtool Intro: Previous Work, http:/ /www.lingsoft/fi/doc/nptool/intro/previous.html. |
NPtool Intro: NPtool inOutline, http:/ /www.lingsoft/fi/doc/nptool/intro/outline.html. |
NPtool Intro: Syntactic Description, http:/ /www.lingoft.fi/doc/nptool/intro/syntax.html. |
NPtool Intro: Performance, http:/ /www.lingsoft/fi/doc/nptool/intro/performance.html. |
NPtool Intro: Conclusion and Acknowledgements, http:/ /www.lingsoft.fi/doc/nptool/intro/conculsion.html. |
Orbital Technologies: Our Focus, http:/ /www.oribtal-tech.com/. |
Orbital Technologies: Orbital Products, http:/ /www.orbital-tech.com/products.html. |
Orbital Technologies: Organik KnowledgeWare, http://www.oribtal-tech.com/organikkw.html. |
Orbital Technologies: About Orbital Technologies, http:/ /www.orbital-tech.com/about.html. |
Orbital Technologies: Organik Persona Server, http:/ /www.orbital-tech.com/organikps.html. |
Orbital Technologies: Corporate Fact Sheet, http://www.orbital-tech.com. |
Orbital Technologies: Orbital Organik White Paper, Jul. 1997, http:/ /www.oribtal-tech.com/. |
“Applying Evolutionary Algorithms to the Problem of Information Filtering”, Tjoa et al., Proceedings of the 8th International Workshop on Database and Expert System, Sep. 1-2, 1997, pp. 450-458. |
“Distributing PeCo-Mediator: Finding Partners via Personal Connections,” IEEE International Conference on Systems, Man, and Cybermatics, 1996, vol. 1, pp. 802-807, Oct. 14-17, 1996. |
Open Sesame: Press, http:/ /opensesame.com/press.cfm. |
Open Sesame: Press, Reviews, http:/ /www.opensesame.com/pr—02.html. |
Autonomy Knowledge Management Products, http:/ /www.agentware.com. |
Autonomy Latest News, Autonomy Home Page, http:/ /www:agentware.com. |
Autonomy Knowledge Server Data Sheet, http:/ /www.agentware.com. |
Autonomy Knowledge Update Data Sheet, http:/ /www.agentware.com. |
The Technology Behind Autonomy Agentware, Autonomy Technology Page, http:/ /www.agentware.com. |
Autonomy Agentware Technology White Paper, http:/ /www.agentware.com. |
“Autonomy Launches New Knowledge Management Products to Help Companies Leverage Employee Expertise, Late-Breaking News and Existing Information Archives”, Autonomy Press Release, Feb. 17, 1998, http:/ /www.agentware.com. |
“Autonomy Ships Agentware Products for Knowledge Management”, Autonomy Press Release, Apr. 14, 1998, http:/ /www.agentware.com. |
Orbital Software : Organik : Introduction “A Multitude of Possibilities” Sep. 6, 2000. http:/ /www.orbitalsw.com/product/product.htm. |
Autonomy, Value Proposition, Sep. 6, 2000. http:/ /www.autonomy.com/valuproposition.html. |
Abuzz—Beehive Beta Program, Beehive, Aug. 10, 1998, http:/ /www.buzz.com/home/demos.htm. |
McCandless, “Managing your privacy in an on-line world”, Internet Services, MIT Laboratory for Computer Science, (2 pages), Jan.-Feb. 1997. |
Didier Bourigault et al., “Term Extraction + Term Clustering: An Integrated Platform for Computer-Aided Terminology”, Proceedings of EACL 1999, pp. 15-22. |
“Clustering: An Introduction”, A Tutorial on Clustering Algorithms, http:/home.dei.polimi.it/matteucc/Clustering/tutorial—html/, downloaded on Mar. 10, 2008, 5 pages. |
NPtool Intro: Uses of a Noun Phrase Parser, http://www.lingsoft.fi/doc/nptool/intro/uses.html, downloaded Jul. 27, 1998, 1 page. |
Natrificial: The Brain: Reviews, The Brain Press Reviews, http://www.natrificial.com/Brain/reviews.html, downloaded Sep. 4, 1998, 1 page. |
Natrifical: The Brain: Info, “The Web at the Speed of Thought”, http://www.natrificial.com/Brain/info—03.html, Sep. 4, 1998, 1 page. |
Hensley et al., “Proposal for an Open Profiling Standard”, NOTE-OPS-FrameWork.html, submitted to W3C on Jun. 2, 1997, XP-002279477, 12 pages. |
Data Sources, Telecomm Software, Software, First Edition, 1998, 6 pages. |
David Golberg et al., “Using Collaborative Filtering to Weave and Information Tapestry”, Communications of the ACM, Dec. 1992, vol. 35, No. 12, pp. 61-70. |
PCT Search Report for PCT/US99/19949, dated Dec. 7, 1999, 6 pages. |
“Beehive”, Abuzz—Beehive Benefits, http://www.abuzz.com/home/benefits.htm. |
Supplementary European Search Report for EPO Application No. EP 99 94 5206, dated Oct. 24, 2006, 2 pgs. |
Patent Cooperation Treaty's Written Opinion for International application No. PCT/US99/19949, dated Oct. 19, 2000, 5 pgs. |
PCT Notification of Transmittal of International Preliminary Examination Report for PCT/US99/19949, dated Jan. 30, 2001, 6 pgs. |
PCT Notification of Transmittal of the International Search Report or the Declaration for PCT/US99/19482 Containing International Search Report, dated Nov. 17, 1999, 4 pgs. |
Patent Cooperation Treaty's Written Opinion for International application No. PCT/US99/19482, dated Jul. 24, 2000, 5 pgs. |
PCT Notification of Transmittal of International Preliminary Examination Report for PCT/US99/19482, dated Jan. 16, 2001, 6 pgs. |
K. Moore, “MIME (Multipurpose Internet Mail Extensions) Part Two: Message Header Extensions for Non-ASCII Text,” RFC1522, University of Tennessee, 11 pages, Sep. 1993. |
Maltz, David, et al., Association for Computing Machinery: “Pointing the Way: Active Collabrative Filtering”; CHI '95 Mosaic of Creativity Confernce Proceedings, May 7-11, 1995; pp. 202-209. |
Notification of Transmittal of International Preliminary Examination Report for PCT/US99/20672, dated Nov. 19, 2001, 6 pages. |
Written Opinion for PCT/US99/20672, dated May 10, 2001, 6 pages. |
PCT International Search Report for PCT/US99/20672, dated Dec. 16, 1999, 5 pages. |
Written Opinion for PCT/US99/20487, dated Aug. 3, 2000, 5 pages. |
Notification of Transmittal of International Preliminary Examination Report for PCT/US99/20487, dated Jan. 10, 2001, 5 pages. |
PCT International Search Report for PCT/US99/20487, dated Nov. 17, 1999, 4 pages. |
Notification of Transmittal of International Preliminary Examination Report for PCT/US99/21110, dated Feb. 21, 2001, 6 pages. |
Written Opinion for PCT/US99/21110, dated Sep. 28, 2000, 3 pages. |
PCT International Search Report for PCT/US99/21110, dated Jan. 24, 2000, 8 pages. |
PCT International Search Report for PCT/US9921112, dated Apr. 25, 2000, 4 pages. |
Notification of Transmittal of International Preliminary Examination Report for PCT/US99/21112, dated Feb. 21, 2001, 6 pages. |
PCT International Search Report for PCT/US99/19949, dated Dec. 7, 1999, 5 pgs. |