Patent Application
20130086167
Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services such as social networking, mobile communication services, and the like. As the popularity and variety of these types of services increase, users are finding an increased need to manage their personal identities when engaged in online-based social interactions. For example, on many social networking services, identity tokens (e.g., pictures, avatars, icons, etc.) are used to represent users with the services. Traditionally, users can either use a default identity token or spend time personalizing the identity token. However, as the number of services and/or applications using such identity tokens increase, users may often find it too burdensome to personalize and/or maintain their identity tokens. Accordingly, service providers and device manufacturers face significant technical challenges to enable efficient identity expression in digital media that can be used as, for instance, identity tokens for services and applications.
Therefore, there is a need for an approach for facilitating and reducing user burden for creating and/or otherwise maintaining identity tokens for personalizing identity expression.
According to one embodiment, a method comprises processing and/or facilitating a processing of contextual data associated with a user, one or more devices associated with the user, or a combination thereof to determine one more or user personality characteristics. The method also comprises causing, at least in part, a generation of one or more identity tokens based, at least in part, on the one or more user personality characteristics. In one embodiment, the one or more identity tokens represent the user in one or more services, one or more applications, or a combination thereof.
According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause, at least in part, the apparatus to process and/or facilitate a processing of contextual data associated with a user, one or more devices associated with the user, or a combination thereof to determine one more or user personality characteristics. The apparatus also causes, at least in part, a generation of one or more identity tokens based, at least in part, on the one or more user personality characteristics. In one embodiment, the one or more identity tokens represent the user in one or more services, one or more applications, or a combination thereof.
According to another embodiment, a computer-readable storage medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause, at least in part, an apparatus to process and/or facilitate a processing of contextual data associated with a user, one or more devices associated with the user, or a combination thereof to determine one more or user personality characteristics. The apparatus also causes, at least in part, a generation of one or more identity tokens based, at least in part, on the one or more user personality characteristics. In one embodiment, the one or more identity tokens represent the user in one or more services, one or more applications, or a combination thereof.
According to another embodiment, an apparatus comprises means for processing and/or facilitating a processing of contextual data associated with a user, one or more devices associated with the user, or a combination thereof to determine one more or user personality characteristics. The apparatus also comprises means for causing, at least in part, a generation of one or more identity tokens based, at least in part, on the one or more user personality characteristics. In one embodiment, the one or more identity tokens represent the user in one or more services, one or more applications, or a combination thereof.
In addition, for various example embodiments of the invention, the following is applicable: a method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on (or derived at least in part from) any one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.
For various example embodiments of the invention, the following is also applicable: a method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform any one or any combination of network or service provider methods (or processes) disclosed in this application.
For various example embodiments of the invention, the following is also applicable: a method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on data and/or information resulting from one or any combination of methods or processes disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.
For various example embodiments of the invention, the following is also applicable: a method comprising creating and/or modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based at least in part on data and/or information resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.
In various example embodiments, the methods (or processes) can be accomplished on the service provider side or on the mobile device side or in any shared way between service provider and mobile device with actions being performed on both sides.
For various example embodiments, the following is applicable: An apparatus comprising means for performing the method of any of originally filed claims 1-10, 21-30, and 46-48.
Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings:
Examples of a method, apparatus, and computer program for providing identity expression in digital media are disclosed. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.
Although various embodiments are discussed with respect to graphically-based identity tokens (e.g., avatars, icons, images, etc.), it is contemplated that the various embodiments are also applicable to identity tokens based graphics, images, audio, text, badges, multimedia, or any other type of digital media. By way of example, identity tokens can be presented (e.g., displayed, played back, etc.) in any number of services as a representation of the user.
However, the need for identity expression and management can often become overly cumbersome for users, particularly when users engage in multiple services or wish to select identity tokens to reflect behavioral or personality characteristics that can change with the users context or that can evolve over time. Historically, selecting identity tokens for services and/or applications involves manually selecting a representative picture. If the user wants to update the identity token (e.g., to reflect new interests, new behaviors, etc.), the user typically would have to manually reselect new identity tokens to use. Overtime, the burden (e.g., burden associated with tracking which services need identity tokens, generating media for incorporation into such tokens, etc.) can quickly overwhelm many users, thereby discouraging their use of such services.
To address this problem, a system 100 of
As used in the descriptions of the various embodiments described herein, the contextual data refers, for instance, to data that indicates the state of a device, state of the device environment and/or the inferred state of a user of the device. The states indicated by the context are, for instance, described according to one or more “contextual parameters” including time, recent applications running on the device, recent World Wide Web pages presented on the device, keywords in current communications (such as emails, SMS messages, IM messages), current and recent locations of the device (e.g., from a global positioning system, GPS, or cell tower identifier), environment temperature, ambient light, movement, transportation activity (e.g., driving a car, riding the metro, walking, cycling, etc.), activity (e.g., eating at a restaurant, drinking at a bar, watching a movie at a cinema, watching a video at home or at a friend's house, exercising at a gymnasium, travelling on a business trip, travelling on vacation, etc.), emotional state (e.g., happy, busy, calm, rushed, etc.), interests (e.g., music type, sport played, sports watched), contacts, or contact groupings (e.g., family, friends, colleagues, etc.), among others, or some combination thereof.
In one example use case, a mobile phone of a target user collects contextual data, such as that pertaining to location or proximity-based social interaction of the target user. Using the collected data, the system 100 derives one or more personality characteristics or types. In one embodiment, the personality characteristics can be specified from predetermined categories or can be derived based on the processing. For instance, if location data is accessible to the system 100, inferences can be made about whether the target user is a home person, work person, or party person. The resulting personality characteristics is then converted to an identity token (e.g., a graphical identity token), which can be displayed in a digital media application or service such as social networking services.
In one embodiment, the identity token can evolve over time, based on behavioral or personality changes detected in collected contextual data. By way of example, depending on the preferences of the user, the identity token can be generated to reflect real-time or substantially real-time behavioral or personality characteristics (e.g., a short term time period or scale for collecting contextual data) or at the other extreme, based on long term stable characteristics of the user (e.g., a longer time period for collecting contextual data).
In one embodiment, the system 100 enables unidirectional or bidirectional communication between identity token creation and the services and/or applications using the identity tokens. For example, in one embodiment, on creating an identity token, the system 100 can transmit the identity token to one or more services and/or applications designated by the user without further interaction. In another embodiment, the system 100 may receive feedback from the service and/or application regarding the popularity of a generated identity token. In yet another embodiment, the system 100 may interact with the service or application to determine what data modalities of the contextual data should be processed for a given service or application. For example, a data modality can be a subset of the contextual data such as mobility data, application usage data, search history data, activity data, sensor (e.g., gyroscopes, accelerometers, proximity sensors, etc.) data, and the like. For example, a sports tracking application may be specify data modalities related to physical activity such as mobility data, activity data, sensor data, etc. In this way, the system 100 can determine behavioral or personality characteristics specific to the data modalities of most relevance to a particular service or application.
In one use case, location data may be a data modality of main importance or relevance. For instance, in this use case, a user may activity an identity tracking service on his or her mobile device using a specific application. By activating the service, the user has also consented to automated collection of contextual data. In some embodiments, to adhere to privacy considerations, the contextual data collected by the mobile phone is not uploaded to the server, but instead, as much as possible of the analysis or processing of the sensitive data performed locally at the mobile device.
Once the service has been activated, the identity tracking service or client of the service instructs the mobile phone to start collecting contextual data (e.g., in this case, location data) in a continuous fashion, over data modalities such as GPS, Cell ID, geolocalized WiFi access points, etc. In one embodiment, the continuously collected location data is analyzed to identify locations in which the user spends time. For example, these locations may be designated as location anchors.
In some embodiments, the system 100 may attempt to semantically group the location anchors or otherwise determine a semantic meaning or relationship of the location anchors. The following list provides example techniques for determining semantic meaning:
Once the semantics has been derived for as many locations anchors as possible, the personality type of the user can be determined. In one embodiment, the following logic listed in Table 1 can be used:
The system 100 can then render a user interface with the determined personality type and/or identity tokens for presentation to the user. In one embodiment, the identity tracking service or client enables the user to configure parameters related to the creation and/or distribution of the identity tokens. For example, the user may configure the following parameters:
Once the user has configured the values using the identity tracking service, the system 100 starts communication with the selected services or applications. In one embodiment, the type of identity token to be displayed in any given service or application is communicated, as well as accompanying parameters, such as privacy settings. In addition, the identity tracking service sends updates to the selected services and/or applications when the identity tokens needs to be change (e.g., based on the frequency configured by the user). Similarly, in one embodiment, the services and/or applications can send information back to the identity tracking service or client on a regular basis. As discussed above, this information may include, for instance, statistics pertaining to the popularity of the identity tokens. For example, the user might want to track the frequency at which other service users are commenting on the user's identity tokens.
Although the embodiments of the use case described above are based on location data, it is contemplated that other contextual data types or modalities can be used to determine personality or behavioral characteristics for generating the identity tokens. Examples of other contextual data types or modalities include, but are not limited to:
As shown in
In one embodiment, the profile database 117 stores the contextual data as part of user profile information. In some embodiments, context-based user profile can also provide for a layered structure to control privacy and/or security of the profile. For example, user contexts and associated user preferences or settings can be grouped according to different classes that are associated with different levels of privacy and/or security controls. In this way, a user can grant access to various portions of the user profile on a class-by-class level to advantageously enable more efficient designation and control of privacy and/or security of user contexts, particularly as the number of contexts embedded in the user profile increases.
In yet another embodiment, the context-based user profile supports profile adaption and extensibility for applicability to a wide range of applications and/or services. For example, the contexts, applications, services, etc. may express context information according to different ontologies or vocabularies. The system 100 can translate the information among the various contexts, applications, services, etc. so that like information can be identified and processed. In this way, the system 100 need not manage or impose a system-wide ontology or vocabulary. As used herein, an ontology refers, for instance, to a defined schema for specifying the various context information, parameters, controls, structures, rules, mechanisms, and the like for expressing profile information.
In another embodiment, the system 100 makes the user profile available to applications, services, content providers, etc. through APIs or other interfaces so that context-based user preferences can be taken into account when performing functions, configuring settings, delivering services, providing content, etc. In this way, the advanced context-based user profile can be uniquely associated with a user to express preferences, settings, etc. for content, applications, services, and the like consumed, used, or initiated by or on behalf of the user.
In addition, the user identity platform 103 and/or the identity managers 107 can collect contextual data from one or more respective sensors 119a-119n (a sound recorder, light sensor, global positioning system (GPS) device, temperature sensor, motion sensor, accelerometer, and/or any other device that can be used to collect information about surrounding environments associated with the UE 101). The collected contextual data then be used to determine one or more behavioral or personality characteristics for generating the identity tokens.
In one embodiment, the services/applications 113a-113m comprise the server-side components corresponding to the applications 109a-109n operating within the UEs 101. In one embodiment, the service platform 111, the services/applications 113a-113m, the applications 109a-109n, or a combination thereof have access to, provide, deliver, etc. one or more items associated with the content providers 115a-115k. In other words, content and/or items are delivered from the content providers 115a-115k to the applications 109a-109n or the UEs 101 through the service platform 111 and/or the services/applications 113a-113n. In one embodiment, the delivery and/or execution of these content, services, applications, etc. are collected as contextual data associated with the UE 101, a user of the UE 101, other UEs 101, other users, or a combination thereof.
In one embodiment, contextual data maybe collected as one or more contextual records. By way of example, a context record includes, at least in part, all context data and interaction data (e.g., date, time of day, location, activity, etc.) collected at a specific time. In one embodiment, the interaction data may serve as contextual parameters for stratifying the contextual data for processing. For example, contextual records maybe stratified by time of day, so that personality characteristics derived from the stratified data can also be correlated with the time of day or any other selected contextual parameter. Accordingly, the system 100 can also generate identity tokens to reflect the specific contextual parameter (e.g., one identity token reflecting a different personality characteristic associated with the morning, and another identity token associated with a user's personality at night time).
By way of example, the context record may contain or describe several contexts wherein each context is a subset of the context data included in the context record. For example, given a context record including a time, context data, and interaction data, e.g., [time=t1, Context Data=<(Work Day), (Evening), (High Speed), (High Audio Level)>, Interaction=Play Games], various combinations or permutations of the context data can yield various contexts such as: (1) <(Evening)>, (2) <High Speed>, (3) <(Work Day), (Evening)>, etc. Further, in one embodiment, the contexts from the context data may be arranged according to the timestamp of each record and may be placed into context groups based on, for instance, the similarity of the contexts (e.g., whether the contexts associated with the same location, environmental condition, user activity, etc.). For example, a context can be any subset of the context data arranged in any combination, which can then be organized as context groups or patterns. The combinations of the contexts with respect to the time stamp may be referred as context patterns, and same or similar context patterns may be grouped into context groups.
The behavior patterns or personality characteristics of the user may be determined based on the association of the context groups (or context patterns) and the interaction data. Generally, the context data is generally continuous over time and is volatile, whereas the interaction data is sparse over time. For example, when both the contexts and the interaction data are organized by timestamps representing different time intervals over a period of time, there may be many instances where there may be some context data but no interaction data corresponding to a certain time stamp because the user generally does not continuously interact with the UE 101. Thus, the system 100 determines the time range over which a common context occurs and places the continuously recorded contexts into context groups associated with the common context. In this way, and the system 100 can associate the contexts (e.g., according to the time ranges represented by the context records in the context groups) with the interaction data, instead of associating individual context records, for determining behavior patterns.
By way of example, the communication network 105 of system 100 includes one or more networks such as a data network (not shown), a wireless network (not shown), a telephony network (not shown), or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short range wireless network, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiber-optic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN), Bluetooth®, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), and the like, or any combination thereof.
The UE 101 is any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the UE 101 can support any type of interface to the user (such as “wearable” circuitry, etc.).
By way of example, the UE 101, the user identity platform 103, and the identity manager 107 communicate with each other and other components of the communication network 105 using well known, new or still developing protocols. In this context, a protocol includes a set of rules defining how the network nodes within the communication network 105 interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model.
Communications between the network nodes are typically effected by exchanging discrete packets of data. Each packet typically comprises (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol typically indicates a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, typically include a physical (layer 1) header, a data-link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application headers (layer 5, layer 6 and layer 7) as defined by the OSI Reference Model.
In one embodiment, the identity manager 107 and the user identity platform 103 interact according to a client-server model. It is noted that the client-server model of computer process interaction is widely known and used. According to the client-server model, a client process sends a message including a request to a server process, and the server process responds by providing a service. The server process may also return a message with a response to the client process. Often the client process and server process execute on different computer devices, called hosts, and communicate via a network using one or more protocols for network communications. The term “server” is conventionally used to refer to the process that provides the service, or the host computer on which the process operates. Similarly, the term “client” is conventionally used to refer to the process that makes the request, or the host computer on which the process operates. As used herein, the terms “client” and “server” refer to the processes, rather than the host computers, unless otherwise clear from the context. In addition, the process performed by a server can be broken up to run as multiple processes on multiple hosts (sometimes called tiers) for reasons that include reliability, scalability, and redundancy, among others.
As shown, the identity platform 103 includes one or more user Personality Inference Engines (PIEs) 201a-201n (also collectively referred as PIEs 201) that use, for instance, advanced machine learning techniques such as collaborative filtering to process user and application data (e.g., in the user and application database 203) to support determination of user behavior patterns, personality characteristics, contexts, etc. for generating identity tokens. These user behavior or personality characteristicss are then mapped to certain identity tokens for identity expression.
In certain embodiments, there may be several PIEs 201 in a UE 101 with each PIE 201 concentrating on one or more particular personality characteristic or data modality. In other words, each PIE 201 may include specific algorithms and or access specific data to infer user characteristic information from a particular type or source of user behaviors, personalities, or contexts. For example, one PIE 201 may concentrate on making inferences about personality characteristics associated location or mobility data, whereas another PIE 201 may concentrate on making inferences about personality characteristics associated with sports activities.
The user identity platform 103 also includes one or more Context Inference Engines (CIEs) 205a-205m (also collectively referred to as CIEs 205) that function similarly to the PIEs 201 except that the data being used are current context information that depict, for instance, user, system, and/or environmental contexts or context information. In one embodiment, the CIE 205 uses respective primary context sources 207a-207m (also collectively referred to as context sources 207) and related inferences to determine latent contexts or personality characteristics associated with a UE 101 or an associated user. For example, the CIE 205 can combine several sources or types of context information to form a higher level hypothesis with respect to what contexts or characteristics to associate with the user. Like, the PIEs 201, the user identity platform 103 can include one or more CIEs 205 that concentrate on generating specific types of contexts or context inferences.
In one embodiment, the context embedder 209 then combines input from the PIEs 201 and the CIEs 205s and integrates the data in a user personality profile according to certain integration rules. By way of example, the integration rules generally specify what data modalities or contextual data types are of relevance to a given service or application. The rules may also be used to stratify the contextual data based on one or more contextual parameters (e.g., location, time, activity, etc.). inferred contexts and associated user preferences that can be used to pre-fill or otherwise populate context fields in the context-based user profile to describe a user's personality characteristics.
In one embodiment, the context embedder 209 chooses an appropriate template or rule based on input from the PIEs 201 and integrates/fills the selected template with appropriate context data if available to determine user personality characteristics. The context embedder 209 then feeds the information to the identity token builder (ITB) 211. It is noted that in one embodiment, the PIEs 201, the CIEs 205, and the context embedder 209 can be a single integrated entity and may rely on a single database (e.g., a single database combining, for instance, data from the user and application data database 203 and context sources 207). The separate modules are shown in
The ITB 211 then generates one or more identity tokens based on the personality characteristics in the profile by the PIEs 201, the CIEs 205, and the context embedder 209. In one embodiment, the user identity platform 103 uses an XML based profile that enables efficient processing. As previously noted, it is contemplated that any other data format or structure may be used. In one embodiment, the context ontologies and vocabulary definitions (VOCs) module 210 provides definitions and translation of vocabularies used by the different PIEs 201 and CIEs 205 and is used in resolving name conflicts of the various embedded contexts of the personality characteristics profile and the various context related inputs (e.g., manual inputs from the profile user interface (UI) 213). In one embodiment, the profile UI 213 can be part of client applications (e.g., applications 109) or a UI application on its own. The profile UI 213 is used to manually enter user data that is not or cannot be inferred by the PIEs 201 and/or the CIEs 205. By way of example, the profile UI 213 is also used to edit or confirm profile data and identity tokens as well as change privacy settings and levels.
Once the identity tokens are generated, the user identity platform 103 can store the identity tokens locally at the UE 101 or remotely over the communication network 105 (e.g., the profile database 117). The identity tokens are then made accessible or otherwise usable by various applications and services (e.g., applications 109, service platform 111, services/applications 113, etc.). In one embodiment, communications with the applications and/or services are by way of the application programming interfaces (APIs) 215.
In one embodiment, the identity tokens can include any digital media representative of the user's identity (e.g., graphics, audio, text, multimedia, etc.). The identity tokens are generated on the client (e.g., using the identity manager 107) and/or remotely on the server side (e.g., using the user identity platform 103). In some embodiments, generating an identity token includes selecting media representative of the personality characteristics of the user and compositing the media. As previously noted, the identity tokens can be determined based on specific data modalities or types of the contextual data that is most relevant to a particular service or application. In another embodiment, multiple identity tokens may be generated for a given service or application for use under different contexts or situations (e.g., while at work, during certain hours, while performing a particular activity, etc.). In addition, the ITB 211 may also generate the identity tokens based on selected themes that reflect user interests or other contexts (e.g., holidays, seasons, etc.).
In some embodiments, the user identity platform 103 determines whether specific or certain data modalities of the contextual data are to be processed for generating an identity token (step 303). For example, specific modalities or types of contextual data may be configured by a user, determined by a user's privacy settings, or specified by the service or application that is to receive the identity token. In this case, the user identity platform 103 determines one or more modalities of the contextual data associated with respective ones of the one or more services, the one or more applications, or a combination thereof (step 305). For example, in one embodiment, the user identity platform 103 does not expose any data modality or type that is not requested or authorized for access by the service or application. In addition, the selection of specific modalities enables the user identity platform 103 to customize the identity token for a particular service or application.
In step 307, the user identity platform 103 determines whether to stratify the contextual data for processing. If the data are to be stratified, the user identity platform 103 causes, at least in part, a stratification of the contextual data into one or more subsets based, at least in part, on one or more contextual parameters. In one embodiment, the one or more contextual parameters include, at least in part, a location parameter, a temporal parameter, an activity parameter, or a combination thereof. For example, the data can be stratified based on location, time, activity, etc. (step 309). In step 311, the user identity platform 101 processes and/or facilitates a processing of the contextual data (e.g., either stratified or unstratified) to determine one or more semantic groupings of one or more portions of the contextual data. The semantic groupings, for instance, or determined based on processing to infer meaning from the contextual data so that data related or otherwise associated with a contexts of similar meanings are grouped together.
The user identity platform 103 then processes and/or facilitates a processing of the contextual data (e.g., the semantically grouped contextual data) associated with a user, one or more devices associated with the user, or a combination thereof to determine one more or user personality characteristics (step 313). The user identity platform 103 then causes, at least in part, a generation of one or more identity tokens based, at least in part, on the one or more user personality characteristics (step 315). As previously described, the one or more identity tokens represent the user in one or more services, one or more applications, or a combination thereof. In some embodiments, the user identity platform 103 can also cause, at least in part, a rendering of at least one user interface for at least one of: (1) presenting the one or more personality characteristics for confirmation or modification; (2) presenting the one or more identity tokens for confirmation or modification; (3) presenting the one or more services, the one or more applications, or a combination thereof for confirmation or modification; (4) determining one or more privacy settings associated with the contextual data, the one or more identity tokens, or a combination thereof; and the like.
Next, the user identity platform 103 causes, at least in part, a transmission of the one or more identity tokens to one or more services or applications for use in representing the user. By way of example, the transmission may be performed directly via an application programming interface, transmitted via one or more communication protocols (e.g., emails, instant messaging, text messaging, etc.), or conveyed in any other way from the user identity platform 103 to the appropriate applications or services. The user identity platform 103 can also determine popularity information of the one or more identity tokens with respect to the one or more services, the one or more applications, or a combination thereof (step 319). In one embodiment, the popularity information can be presented to the user to aid in determining what identity tokens to generate or select for use.
Identity tokens 403 and 405 are examples of identity tokens generated for specific personality categories. For example, identity token 403 is generated for a user whose personality characteristics indicate that the user is a “Party Animal”. The identity token 403 further provides a graphical representation of the personality characteristic and specifies that the service using this token is the “iDentity” service. Identity token 405 is another example identity token generated for a user whose personality characteristics indicate that the user is a “Workaholic”. The identity token 405 provides a graphical representation of “Workaholic” and also indicates that the token is for use in the “iDentity” service or application.
The processes described herein for providing identity expression in media may be advantageously implemented via software, hardware, firmware or a combination of software and/or firmware and/or hardware. For example, the processes described herein, may be advantageously implemented via processor(s), Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc. Such exemplary hardware for performing the described functions is detailed below.
A bus 510 includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus 510. One or more processors 502 for processing information are coupled with the bus 510.
A processor (or multiple processors) 502 performs a set of operations on information as specified by computer program code related to providing identity expression in media. The computer program code is a set of instructions or statements providing instructions for the operation of the processor and/or the computer system to perform specified functions. The code, for example, may be written in a computer programming language that is compiled into a native instruction set of the processor. The code may also be written directly using the native instruction set (e.g., machine language). The set of operations include bringing information in from the bus 510 and placing information on the bus 510. The set of operations also typically include comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor 502, such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination.
Computer system 500 also includes a memory 504 coupled to bus 510. The memory 504, such as a random access memory (RAM) or any other dynamic storage device, stores information including processor instructions for providing identity expression in media. Dynamic memory allows information stored therein to be changed by the computer system 500. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory 504 is also used by the processor 502 to store temporary values during execution of processor instructions. The computer system 500 also includes a read only memory (ROM) 506 or any other static storage device coupled to the bus 510 for storing static information, including instructions, that is not changed by the computer system 500. Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus 510 is a non-volatile (persistent) storage device 508, such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system 500 is turned off or otherwise loses power.
Information, including instructions for providing identity expression in media, is provided to the bus 510 for use by the processor from an external input device 512, such as a keyboard containing alphanumeric keys operated by a human user, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system 500. Other external devices coupled to bus 510, used primarily for interacting with humans, include a display device 514, such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a plasma screen, or a printer for presenting text or images, and a pointing device 516, such as a mouse, a trackball, cursor direction keys, or a motion sensor, for controlling a position of a small cursor image presented on the display 514 and issuing commands associated with graphical elements presented on the display 514. In some embodiments, for example, in embodiments in which the computer system 500 performs all functions automatically without human input, one or more of external input device 512, display device 514 and pointing device 516 is omitted.
In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC) 520, is coupled to bus 510. The special purpose hardware is configured to perform operations not performed by processor 502 quickly enough for special purposes. Examples of ASICs include graphics accelerator cards for generating images for display 514, cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware.
Computer system 500 also includes one or more instances of a communications interface 570 coupled to bus 510. Communication interface 570 provides a one-way or two-way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link 578 that is connected to a local network 580 to which a variety of external devices with their own processors are connected. For example, communication interface 570 may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface 570 is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface 570 is a cable modem that converts signals on bus 510 into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface 570 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface 570 sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface 570 includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface 570 enables connection to the communication network 105 for providing identity expression in media to the UE 101.
The term “computer-readable medium” as used herein refers to any medium that participates in providing information to processor 502, including instructions for execution. Such a medium may take many forms, including, but not limited to computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Non-transitory media, such as non-volatile media, include, for example, optical or magnetic disks, such as storage device 508. Volatile media include, for example, dynamic memory 504. Transmission media include, for example, twisted pair cables, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. The term computer-readable storage medium is used herein to refer to any computer-readable medium except transmission media.
Logic encoded in one or more tangible media includes one or both of processor instructions on a computer-readable storage media and special purpose hardware, such as ASIC 520.
Network link 578 typically provides information communication using transmission media through one or more networks to other devices that use or process the information. For example, network link 578 may provide a connection through local network 580 to a host computer 582 or to equipment 584 operated by an Internet Service Provider (ISP). ISP equipment 584 in turn provides data communication services through the public, world-wide packet-switching communication network of networks now commonly referred to as the Internet 590.
A computer called a server host 592 connected to the Internet hosts a process that provides a service in response to information received over the Internet. For example, server host 592 hosts a process that provides information representing video data for presentation at display 514. It is contemplated that the components of system 500 can be deployed in various configurations within other computer systems, e.g., host 582 and server 592.
At least some embodiments of the invention are related to the use of computer system 500 for implementing some or all of the techniques described herein. According to one embodiment of the invention, those techniques are performed by computer system 500 in response to processor 502 executing one or more sequences of one or more processor instructions contained in memory 504. Such instructions, also called computer instructions, software and program code, may be read into memory 504 from another computer-readable medium such as storage device 508 or network link 578. Execution of the sequences of instructions contained in memory 504 causes processor 502 to perform one or more of the method steps described herein. In alternative embodiments, hardware, such as ASIC 520, may be used in place of or in combination with software to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware and software, unless otherwise explicitly stated herein.
The signals transmitted over network link 578 and other networks through communications interface 570, carry information to and from computer system 500. Computer system 500 can send and receive information, including program code, through the networks 580, 590 among others, through network link 578 and communications interface 570. In an example using the Internet 590, a server host 592 transmits program code for a particular application, requested by a message sent from computer 500, through Internet 590, ISP equipment 584, local network 580 and communications interface 570. The received code may be executed by processor 502 as it is received, or may be stored in memory 504 or in storage device 508 or any other non-volatile storage for later execution, or both. In this manner, computer system 500 may obtain application program code in the form of signals on a carrier wave.
Various forms of computer readable media may be involved in carrying one or more sequence of instructions or data or both to processor 502 for execution. For example, instructions and data may initially be carried on a magnetic disk of a remote computer such as host 582. The remote computer loads the instructions and data into its dynamic memory and sends the instructions and data over a telephone line using a modem. A modem local to the computer system 500 receives the instructions and data on a telephone line and uses an infra-red transmitter to convert the instructions and data to a signal on an infra-red carrier wave serving as the network link 578. An infrared detector serving as communications interface 570 receives the instructions and data carried in the infrared signal and places information representing the instructions and data onto bus 510. Bus 510 carries the information to memory 504 from which processor 502 retrieves and executes the instructions using some of the data sent with the instructions. The instructions and data received in memory 504 may optionally be stored on storage device 508, either before or after execution by the processor 502.
In one embodiment, the chip set or chip 600 includes a communication mechanism such as a bus 601 for passing information among the components of the chip set 600. A processor 603 has connectivity to the bus 601 to execute instructions and process information stored in, for example, a memory 605. The processor 603 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively or in addition, the processor 603 may include one or more microprocessors configured in tandem via the bus 601 to enable independent execution of instructions, pipelining, and multithreading. The processor 603 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP) 607, or one or more application-specific integrated circuits (ASIC) 609. A DSP 607 typically is configured to process real-world signals (e.g., sound) in real time independently of the processor 603. Similarly, an ASIC 609 can be configured to performed specialized functions not easily performed by a more general purpose processor. Other specialized components to aid in performing the inventive functions described herein may include one or more field programmable gate arrays (FPGA) (not shown), one or more controllers (not shown), or one or more other special-purpose computer chips.
In one embodiment, the chip set or chip 600 includes merely one or more processors and some software and/or firmware supporting and/or relating to and/or for the one or more processors.
The processor 603 and accompanying components have connectivity to the memory 605 via the bus 601. The memory 605 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to provide identity expression in media. The memory 605 also stores the data associated with or generated by the execution of the inventive steps.
Pertinent internal components of the telephone include a Main Control Unit (MCU) 703, a Digital Signal Processor (DSP) 705, and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit 707 provides a display to the user in support of various applications and mobile terminal functions that perform or support the steps of providing identity expression in media. The display 707 includes display circuitry configured to display at least a portion of a user interface of the mobile terminal (e.g., mobile telephone). Additionally, the display 707 and display circuitry are configured to facilitate user control of at least some functions of the mobile terminal. An audio function circuitry 709 includes a microphone 711 and microphone amplifier that amplifies the speech signal output from the microphone 711. The amplified speech signal output from the microphone 711 is fed to a coder/decoder (CODEC) 713.
A radio section 715 amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna 717. The power amplifier (PA) 719 and the transmitter/modulation circuitry are operationally responsive to the MCU 703, with an output from the PA 719 coupled to the duplexer 721 or circulator or antenna switch, as known in the art. The PA 719 also couples to a battery interface and power control unit 720.
In use, a user of mobile terminal 701 speaks into the microphone 711 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC) 723. The control unit 703 routes the digital signal into the DSP 705 for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), satellite, and the like, or any combination thereof.
The encoded signals are then routed to an equalizer 725 for compensation of any frequency-dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator 727 combines the signal with a RF signal generated in the RF interface 729. The modulator 727 generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up-converter 731 combines the sine wave output from the modulator 727 with another sine wave generated by a synthesizer 733 to achieve the desired frequency of transmission. The signal is then sent through a PA 719 to increase the signal to an appropriate power level. In practical systems, the PA 719 acts as a variable gain amplifier whose gain is controlled by the DSP 705 from information received from a network base station. The signal is then filtered within the duplexer 721 and optionally sent to an antenna coupler 735 to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna 717 to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, any other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks.
Voice signals transmitted to the mobile terminal 701 are received via antenna 717 and immediately amplified by a low noise amplifier (LNA) 737. A down-converter 739 lowers the carrier frequency while the demodulator 741 strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer 725 and is processed by the DSP 705. A Digital to Analog Converter (DAC) 743 converts the signal and the resulting output is transmitted to the user through the speaker 745, all under control of a Main Control Unit (MCU) 703 which can be implemented as a Central Processing Unit (CPU) (not shown).
The MCU 703 receives various signals including input signals from the keyboard 747. The keyboard 747 and/or the MCU 703 in combination with other user input components (e.g., the microphone 711) comprise a user interface circuitry for managing user input. The MCU 703 runs a user interface software to facilitate user control of at least some functions of the mobile terminal 701 to provide identity expression in media. The MCU 703 also delivers a display command and a switch command to the display 707 and to the speech output switching controller, respectively. Further, the MCU 703 exchanges information with the DSP 705 and can access an optionally incorporated SIM card 749 and a memory 751. In addition, the MCU 703 executes various control functions required of the terminal. The DSP 705 may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP 705 determines the background noise level of the local environment from the signals detected by microphone 711 and sets the gain of microphone 711 to a level selected to compensate for the natural tendency of the user of the mobile terminal 701.
The CODEC 713 includes the ADC 723 and DAC 743. The memory 751 stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device 751 may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, magnetic disk storage, flash memory storage, or any other non-volatile storage medium capable of storing digital data.
An optionally incorporated SIM card 749 carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card 749 serves primarily to identify the mobile terminal 701 on a radio network. The card 749 also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile terminal settings.
While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.
This application claims benefit of the earlier filing date under 35 U.S.C. §119(e) of U.S. Provisional Application Ser. No. 61/541,524 filed Sep. 30, 2011, entitled “Method and Apparatus for Identity Expression in Digital Media,” the entirety of which is incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 61541524 | Sep 2011 | US |
