WO2010148410A2 - Using indicia of interest in a topic for identification and aggregation of content by a semantics-enabled platform - Google Patents

Abstract

A system and method for enhancing assignment of debtor accounts to a plurality of collection parties is presented. The preferred embodiment is capable of optimizing the way by which individual performance entities are assigned to collect on actionable individual debtor accounts by a creditor. An analysis solution uses algorithms to analyze gathered data and to provide a score to each collection party based upon the traits of the individual collection parties, debtor accounts, creditor, externally acquired data, and constraints upon all of the parties involved. The system and method are also capable of enhancing an individual borrower's credit score depending on the risk involved with providing credit to that particular borrower based upon the collectability upon default.

Description

USING INDICIA OF INTEREST IN A TOPIC FOR IDENTIFICATION AND AGGREGATION OF CONTENT BY A SEMANTICS-ENABLED PLATFORM

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No. 61/218,709 filed 19 June 2009, which is hereby incorporated by reference in its entirety.

BACKGROUND

[0002] The search through the vast amount of resources containing electronic content (e.g., digital music, digital video, documents, text files, web pages, time-sensitive content, news articles) in the digital world is increasingly becoming a resource consuming task. The mere task of searching for relevant content of interest and tracking content sources are daunting regardless of whether the scope of the search is within the confines of a local computing system, a private network, a local area network, or the World Wide Web.

BRIEF DESCRIPTION OF THE DRAWINGS

[0003] FIG. 1 illustrates an example block diagram of a host server operating semantics-enabled platform which uses indicia of user interest in a topic detected from user devices on the host site or a third party site for identification and aggregation of content from multiple content providers.

[0004] FIG. 2 depicts an example block diagram of the components of a host server which uses indicia of user interest in a topic detected from user devices on the host site or a third party site for identification and aggregation of content from multiple content providers.

[0005] FIG. 3 depicts an example block diagram of the components of a mobile device that manages interest subscriptions for a user and presents temporally-relevant content to the user based on the interest subscriptions.

[0006] FIG. 4 depicts a flow chart illustrating an example process for a mobile device to manage interest subscriptions for a user and to present temporally-relevant content to the user based on the interest subscriptions.

[0007] FIG. 5 depicts a flow chart illustrating an example process for using indicia of interest in a topic to identify and aggregate, via a semantics-enabled platform, additional content in which a user is potentially interested.

[0008] FIG. 6 depicts a flow chart illustrating an example process for using a semantic representation of a topic to periodically identify content from multiple content sources for presentation to a user.

[0009] FIG. 7 depicts a flow chart illustrating an example process for using a semantic representation of a topic to periodically identify content from multiple content sources for presentation to a user.

[0010] FIG. 8A-8C illustrate example screenshots of a site where indicia of interest relating to a topic can be generated by a user.

[0011] FIG. 9A-C illustrate example screenshots showing how a user can generate an indicia of interest and how interests can be tracked and combined to generate interest collections. [0012] FIG. 10 illustrates an example screenshot of content linked to by the host, the content having a panel through which a user can navigate related content/topics or return to the host site.

[0013] FIG. 11 illustrates an example screenshot of a third party website having features through which indicia of interest can be generated by a user for use by a connected semantics-enabled platform to identify and aggregate additional content to be presented to the user.

[0014] FIG. 12A-C depict example screenshots showing multiple search results and/or filtered search results which can be "Followed" by a user to generate indicia of interest.

[0015] FIG. 12D illustrates a screenshot of an example of a pop-up screen that allows the user to specify the topic/interest to subscribe to.

[0016] FIG. 13 depicts an example of a third-party web page having content that can be tracked by a user using associated features/mechanisms (e.g., the "Follow" buttons).

[0017] FIG. 14 illustrates a screenshot of an example web interface for accessing a tracking agent which can be used to manage subscribed topics/interests and to view/browse the content associated with the subscription.

[0018] FIG. 15A-E depict screenshots of user interfaces on a mobile device showing features (e.g., "FOLLOW" button) allowing users to generate indicia of interest for topics (e.g., channels) and content.

[0019] FIG. 16 shows a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. DETAILED DESCRIPTION

[0020] The following description and drawings are illustrative and are not to be construed as limiting. Numerous specific details are described to provide a thorough understanding of the disclosure. However, in certain instances, well-known or conventional details are not described in order to avoid obscuring the description.

References to one or an embodiment in the present disclosure can be, but not necessarily are, references to the same embodiment; and, such references mean at least one of the embodiments.

[0021] Reference in this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosure. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not other embodiments.

[0022] The terms used in this specification generally have their ordinary meanings in the art, within the context of the disclosure, and in the specific context where each term is used. Certain terms that are used to describe the disclosure are discussed below, or elsewhere in the specification, to provide additional guidance to the practitioner regarding the description of the disclosure. For convenience, certain terms may be highlighted, for example using italics and/or quotation marks. The use of highlighting has no influence on the scope and meaning of a term; the scope and meaning of a term is the same, in the same context, whether or not it is highlighted. It will be appreciated that same thing can be said in more than one way.

[0023] Consequently, alternative language and synonyms may be used for any one or more of the terms discussed herein, nor is any special significance to be placed upon whether or not a term is elaborated or discussed herein. Synonyms for certain terms are provided. A recital of one or more synonyms does not exclude the use of other synonyms. The use of examples anywhere in this specification including examples of any terms discussed herein is illustrative only, and is not intended to further limit the scope and meaning of the disclosure or of any exemplified term. Likewise, the disclosure is not limited to various embodiments given in this specification.

[0024] Without intent to further limit the scope of the disclosure, examples of instruments, apparatus, methods and their related results according to the embodiments of the present disclosure are given below. Note that titles or subtitles may be used in the examples for convenience of a reader, which in no way should limit the scope of the disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In the case of conflict, the present document, including definitions will control.

[0025] Embodiments of the present disclosure include systems and methods for using indicia of interest in a topic for identification and aggregation of content via a semantics-enabled platform.

[0026] In one aspect, the present disclosure relates to a mechanism incorporated in a content source (e.g., online content source) that allows a user to track or follow one or more topics related to the user's interests embodied in the content source.

[0027] In general, the content source can include online and/or offline content sources including but not limited to, web content (e.g., web page and/or website displayed through a browser), content in an email application, and/or content in other types of application (e.g., multimedia, database, enterprise, desktop, mobile applications, hosted applets, etc.). The content type can include by way of example but not limitation, text, document, audio content, video content, image content, a news article, a comment/review entry, a blog entry, etc.

[0028] The content source can be identified by a user through a mechanism (e.g., clicking on a button, selecting a tab, selecting a link, or activating any other types of indicators/selectors, etc.) to indicate to the system, interest in one or more topics embodied in the content source or interest in the content source itself. In addition, the trackable/followable content can be highlighted or linked in such a manner such that when the cursor moves over the link or content, a pop-up window appears allowing the user to select to track the topic/thing and/or indicate interest. [0029] Note that the mechanism (e.g., button, tab, indicator, an icon, an image, etc.) can be implemented using JavaScript, any other type of programming, script, and/or markup language. The mechanism can be automatically configured (e.g., by a web application) or manually added (e.g., by a web developer) in content sources. For example, the mechanism can be configured to be displayed on a web page or web site for each topic, each page, each member/user, each document, each image, or ach video, etc. The mechanism may be configured differently for different content sources.

[0030] In general, the mechanism (e.g., follow button) can be added by anyone to any site. The mechanism, when activated, can trigger an API call to an external host (e.g., social and/or knowledge networking site) which then hosts the followed interest/topic and searches for any content that matches, and notifies the user, for example, on an ongoing basis. The host (e.g., external host including but not limited to social and/or knowledge networking site) may provide a co-branded or white-labeled tracker user interface experience that is either hosted by the external host (e.g., third party host) or by the content provider. The content may or may not appear within the content provider's user interface. For example, the third party can host the tracker and also show the content inside ESPN's site, for example, as if it is part of their site, or it can be external.

[0031] In one embodiment, a content provider may place the Follow button on each item or part of an item or concept that can be followed. Content providers can construct a directory or index of things that may be followed via their site or other partner sites. The providers can also recommend things to be followed to users based on their behavior or what they know of the user's interests.

[0032] Embodiments of the present disclosure describe how users can actively build a topic/channel of interest, using one or more of the semantic ingredients provided by the system. For example, by simply clicking on the 'Follow' button on one or more pages, the user would build a topic of his/her own. In addition to following any existing channels (i.e. entities, relationships, collections, etc.), the system also allows users follow content (e.g. an article, a set of articles, a piece of content on a web page). In this case, the system can derive the semantic representation from the user-selected content.

[0033] For text articles, semantic analysis (i.e. NLP and/or named entity tagging) can be applied to identify main entities and relationships from each article. The system can then aggregate the entities and relationships from multiple articles in user's selection. On more structured data (i.e. a table on a web page), the extraction would depend on how the structure is represented (e.g. in semantic form such as RDF, or in raw HTML which would require some form of scraping). The system can then present the extracted entities, relationships and other semantic representations to the user, such that the user could select from the list and make adjustments.

[0034] FIG. 1 Illustrates an example block diagram of a host server 100 operating semantics-enabled platform which uses indicia of user interest in a topic detected from user devices 102 A-N on the host site or a third party site for identification and aggregation of content from multiple content providers 108 A-N.

[0035] The client devices 102A-N can be any system and/or device, and/or any combination of devices/systems that is able to establish a connection with another device, a server and/or other systems. Client devices 102 A-N each typically include a display and/or other output functionalities to present information and data exchanged among the devices 102 A-N and the host server 100. For example, the client devices 102 A-N can be any of, but are not limited to, a server desktop, a desktop computer, a computer cluster, or portable devices including, a notebook, a laptop computer, a handheld computer, a palmtop computer, a mobile phone, a cell phone, a smart phone, a PDA, a Blackberry device, a Treo, and/or an iPhone, etc. In one embodiment, the client devices 102 A-N, third party host 110, and content providers 108 A-N of electronic content are coupled to a network 106. In some embodiments, the devices 102 A-N and host server 100 may be directly connected to one another.

[0036] In one embodiment, the host server 100 uses user interest in a topic to identify and aggregate content for a specific user. The host server 100 can use the topic to identify additional topics which the user may also be interested in. These additional topics can be identified using keyword-based techniques and/or semantics-based techniques. For example, the host server 100 can use an ontology or taxonomy to identify a hierarchy of topics (e.g., which can be represented as an 'entity' or a 'relationship') which can be used to identify and aggregate additional content for the user.

[0037] Indicia of interest can be user generated, while browsing a site hosted by the host server 100, or third party sites (e.g., hosted by the third-party host 110), for example, by activating features associated with topics themselves or content related to certain topics.

Examples of such features include buttons, tabs, etc. Users can track topics or content via mobile devices as well and leverage the semantics-enabled platform of the host 100 for content recommendation, identification, and/or aggregation. Functions and techniques performed by the host server 100 and the components therein are described in detail with further reference of FIG. 2.

[0038] The client devices 102A-N can be used by users to generate the indicia detected by the host server 100 which indicates interest in a topic or content. The client devices 102 A-N are generally operable to provide user access (e.g., visible access, audible access) to content identified and/or aggregated in detecting user interest in a topic or piece of electronic content, for example via user interface 104A-N displayed on the display units.

[0039] The network 106, over which the client devices 102A-N and the host server

100 communicate, may be a telephonic network, an open network, such as the Internet, or a private network, such as an intranet and/or the extranet. For example, the Internet can provide file transfer, remote log in, email, news, RSS, and other services through any known or convenient protocol, such as, but not limited to the TCP/IP protocol, Open System Interconnections (OSI), FTP, UPnP, iSCSI, NSF, ISDN, PDH, RS-232, SDH, SONET, etc.

[0040] The network 106 can be any collection of distinct networks operating wholly or partially in conjunction to provide connectivity to the client devices 102A-N and the host server 100 and may appear as one or more networks to the serviced systems and devices. In one embodiment, communications to and from the client devices 102 A-N can be achieved by, an open network, such as the Internet, or a private network, such as an intranet and/or the extranet. In one embodiment, communications can be achieved by a secure communications protocol, such as secure sockets layer (SSL), or transport layer security (TLS).

[0041] In addition, communications can be achieved via one or more wireless networks, such as, but not limited to, one or more of a Local Area Network (LAN), Wireless Local Area Network (WLAN), a Personal area network (PAN), a Campus area network (CAN), a Metropolitan area network (MAN), a Wide area network (WAN), a Wireless wide area network (WWAN), Global System for Mobile Communications (GSM), Personal Communications Service (PCS), Digital Advanced Mobile Phone Service (D-Amps), Bluetooth, Wi-Fi, Fixed Wireless Data, 2G, 2.5G, 3G networks, enhanced data rates for GSM evolution (EDGE), General packet radio service (GPRS), enhanced GPRS, messaging protocols such as, TCP/IP, SMS, MMS, extensible messaging and presence protocol (XMPP), real time messaging protocol (RTMP), instant messaging and presence protocol (IMPP), instant messaging, USSD, IRC, or any other wireless data networks or messaging protocols.

[0042] The host server 100 may include internally or be externally coupled to, one or more of any of, a user repository 128, a knowledge repository 130, and/or a user content repository (not shown). The repositories can store software, descriptive data, images, system information, drivers, and/or any other data item utilized by other components of the host server 100 and/or any other servers for operation. The repositories may be managed by a database management system (DBMS), for example but not limited to, Oracle, DB2, Microsoft Access, Microsoft SQL Server, PostgreSQL, MySQL, FileMaker, etc.

[0043] The repositories can be implemented via object-oriented technology and/or via text files, and can be managed by a distributed database management system, an object-oriented database management system (OODBMS) (e.g., ConceptBase, FastDB Main Memory Database Management System, JDOInstruments, ObjectDB, etc.), an object-relational database management system (ORDBMS) (e.g., Informix, OpenLink Virtuoso, VMDS, etc.), a file system, and/or any other convenient or known database management package.

[0044] In some embodiments, the host server 100 is able to provide data to be stored in the user repository 128, the knowledge repository 130, and the user content repository and/or can retrieve data stored in the user repository 128, the knowledge repository 130, and/or the user content repository. The user repository 128 can store user information, user profile, user tags, user interests, any user-generated content (if applicable), user privacy settings, user device information, hardware information, etc.

[0045] The knowledge repository 130 can include, by way of example but not limitation, sets of ontologies, taxonomies and/or folksonomies that can be used by the host server 100 for determining the semantic type or attribute type of topics or interests, etc. In addition, the sets of ontologies, taxonomies and/or folksonomies can be used by the host server 100 in identifying semantic types associated with metadata identified from content sources describing objects and/or the content embodied therein. The ontology set can also be used to identify the type of semantic relationship that exists between the objects/embodied content and the identified semantic types for use by the server 100 in identifying and aggregating content based on user interest in a given topic or set of topics.

[0046] The knowledge repository 130 in some instances, can also include, additional sources of ontologies, user-defined ontologies, customized ontologies, dictionaries, thesauruses, and/or encyclopedias, etc. In one embodiment, location identifier patterns and their associated semantic types and/or attributes are stored in the knowledge repository 130.

[0047] FIG. 2 depicts an example block diagram of the components of a host server 200 which uses indicia of user interest in a topic detected from user devices on the host site or a third party site for identification and aggregation of content from multiple content providers.

[0048] The host server 200 includes a network interface 202, a user interest tracker

204, a type detector module 206, a recommendation module 208, a content identifier 210, a presentation module 212, and/or a mobile platform module 214.

[0049] In one embodiment, the host server 200 is coupled to a user repository 228 and/or a knowledge repository 230. The user repository 228 and the knowledge repository 230 have been described with further reference to the example of FIG. 1.

[0050] Additional or less modules can be included without deviating from the novel art of this disclosure. In addition, each module in the example of FIG. 2 can include any number and combination of sub-modules, and systems, implemented with any combination of hardware components (e.g., ASICS, FPGAs, memory units and/or processors) and/or software modules.

[0051] One embodiment of the host server 200 includes a user interest tracker 204.

The user interest tracker 204 can be any combination of software agents and/or hardware components that are able to detect, identify, determine, track, manage, and/or update user interest in topics, content, types of content, etc.

[0052] The user interest tracker 204 can manage user information such as user information or user profile information including but not limited to, demographic information, interests, level of education, profession, hobbies, etc. User information can be static or dynamically updated by the system. The user module 204 can also detect user action that indicates interest or potential interest in a given topic or piece of content. User interest in a group of topics can be grouped into a collection. For example, a user can create a collection of interest in the topic "Oil Spill" having sub-topics "BP" and "Barack Obama". One embodiment includes a collection manager to track the user's collections of interests. Alternatively, the host server 200 can automatically identify sub-topics based on a given topic specified to be of interest to the user. For example, the host 200 can identify sub-topics "BP" and "Barack Obama" in response to identification of user interest in the topic "Oil Spill".

[0053] In one embodiment, user interest tracker 204 detects indicia of interest (e.g., generated by a user). Such indicia can be explicit or implicit. For example, the user can activate an indicator on a webpage or content displayed via other modes (e.g., email, desktop application, SMS, webpage via a mobile device, and/or cell phone application via a mobile device) to indicate interest in a certain topic or interest in the piece of content. User selectable or activatable indicators (e.g., as shown in the examples in the screenshots of FIG. 8-15) can be displayed on a site hosted by the host server 200 or other sites (e.g., third-party sites in the example of FIG. 11). Such indicators may also be presented via a search engine in conjunction with one or more search results (e.g., FIG. 12A-D).

[0054] In addition, the user interest tracker 204 can detect implicit indicia. For example, tracker 204 can track the user's tagging/bookmarking habits, web browsing habits, time spent on a webpage, website, search queries, etc. to identify implicit indicia of user interest. In addition, the user interest tracker 204 can track browsing behavior such as the frequency with which a user views a particular page or visits a particular site, how active a user is on a site/page (e.g., via browsing, commenting, and/or otherwise interacting with pages or objects), the user's postings on a networking or messaging utility, the user's updates on a networking/messaging utility, the user's shared items with other users, etc.

[0055] One embodiment of the host server 200 includes a type detector module

206. In addition, the module 206 can be any combination of software agents and/or hardware components able to detect the semantic type (e.g., entity, relationship, etc.) of a selected topic of interest. The type detector module 206 assigns a semantic type to topics that can be identified by users as being of interest. [0056] The type detector module 206 can also locate, search, detect, identify, find, retrieve, collect, analyze, and/or aggregate metadata associated electronic objects and/or their embodied content, specifically content that the user has indicated explicit or implicit interest in. The metadata can be used by the server 200 to extract topics that a user may be interested in based on specified interest in a piece of content (e.g., article, news feed, Tweet, etc.)

[0057] In general, metadata associated with objects/embodied content can include, by way of example but not limitation, data regarding or relating to the object/embodied content from any information sources internal and/or external to the host server (e.g., host server 200 of FIG. 2). In addition, the metadata can also be internal in a sense that it is collected from the object itself or the host of the object (e.g., the same host of a web page). In one embodiment, metadata is collected from content sources hosted by various external servers, the host server (e.g., the host server 200 of FIG. 2), and/or a combination of the above.

[0058] In one embodiment, web page metadata is collected from data embedded in

XML, RDF, OWL, RDFA, micro formats to obtain information about web pages. Moreover, the metadata can be collected from electronic content including one or more of, bookmarks, bookmarked content, blog articles, tweets, updates, comments, networking sites (e.g., social networking sites, professional networking sites, knowledge networking sites, Digg, Twine, Delicious, Facebook, MySpace, etc.), networking utilities (e.g.,

Twitter), mobile networking, and/or real time/non-real time messaging (e.g., web-based and/or mobile-device based) utilities, or any content having information about the object (e.g., web page).

[0059] The type detector module 206 can determine a semantic type and/or type of semantic relationship to which metadata or a tag corresponds. Generally, the type detector module 206 can identify the semantic type for metadata or the tag selected for use in tracking user interest and aggregating/identifying content based on user interest.

[0060] Note that semantic types of content in objects (e.g., web pages) can be partially or fully automatically determined by the system or specified by an end user. For example, the semantic type can be automatically determined through topic detection, natural language processing (NLP), speech processing, latent semantics indexing, etc. Semantic types can also be defined by the end user through tagging or annotating the object (e.g., web page) through a user interface in which the object is provided for access.

[0061] In one embodiment, the type detector module 206 detects the semantic entity type or relationship type by mapping the metadata/tag to an ontology or taxonomy set. If the ontological class of a content source (e.g., a web page) is known (e.g., that a given webpage is about restaurants), NLP can be used to map the tags/metatags in the page with an ontology for restaurants. Similarly, on a web page for prescription drugs, if there is a node in the XML template of the web page that maps to "dosage", then node can be mapped to the dosage property of the ontology for prescription drugs.

[0062] One embodiment of module 205 includes a semantic object generator which can generate a semantic object to represent a given topic. For example, the semantic object generator can represent the topic as one or more of: 1) individual entities, 2) categories/facets of entities, 3) groups or collections of entities (e.g. summer new movies, Los Angeles Lakers team members), 4) relationships between entities and/or facets, and 5) keywords and key phrases. Users can create a topic interest using any combination of the above items as ingredients.

[0063] The user interface provided by the system allows users to create their topics of interest. In addition, the system allows identify their preference of content or content sources, either explicitly (users give ratings) or implicitly (by analyzing user click log). Furthermore, in one embodiment, the users can, via the user interface, identify certain content sources that they prefer for a particular topic/channel (e.g. for topics on celebrity gossips, TMZ.com might be a preferred source). During the ranking of the returned results, the system can give more weighting to content from preferred sources. In addition, users could give us feedback on particular pieces of content. For example, we given option to users to rate individual returned article (Like/Don't Like, Thumps up/down, 5-star rating, etc.). Given the feedback, the system can adjust the ranking of the returned content to better tailor to the user's interest.

[0064] One embodiment of the host server 200 includes a topic recommendation module 208. The topic recommendation module 208 can be any combination of software agents and/or hardware components able to recommend potential topics of interest to the user based on detected indicia of interest in a particular topic. [0065] The recommendation module 208, can identify related topics (e.g., which can be represented as entities or relationships) using ontologies stored in the knowledge repository 230, for example. In one embodiment, the topic hierarchy module identifies a hierarchy of topics (entities or relationships) using a known topic of interest. The host 200 can automatically add the related topics and use them in identifying related content to be recommended/pushed to the user. The recommendation module 208 can also prompt the user to determine whether the user is interested in any of these identified related topics. Any suitable method can be implemented to identify the hierarchy of topics, hi one example, given a known topic of interest, the recommendation module 208 identifies related topics by a) using ontologies, and/or b) using NLP/text mining on a corpus of text.

[0066] The topic of interest can be represented in the system as semantic entities and/or relationships, which can be linked to entries in the one or more ontologies. In the ontologies, an entity can include one or more associated facets, which include finely grained characteristics of entities such as types, categories, and/or characteristics, etc. Example facets include actor, politician, basketball player, nation, drug, automobile, and the like. The module 208 can organize the facets into a hierarchical taxonomy, using the "is-a" relation (e.g. facet 'basketball player' is-a 'sports athlete').

[0067] In addition, entities can have properties in the ontology, such as properties that specify relationships with other entities (e.g. a person's spouse, birth place, etc; for a musician, his/her band, music label, top albums and singles, etc; for a NFL football player, the college and professional teams he played for, etc.). Therefore, given an entity associated with the topic of interest, the recommender 208 can identify its facets and relations from the ontology.

[0068] The module 208, in one embodiment, traverses the facet hierarchy to detect, for example, more general or granular facets as related topics. Also, we could traverse the relationship links of the entity in order to identify or detect other related entities (for example, given a NBA basketball player, his current team can be identified; from the team, the team's league/conference can be identified, other team members can be identified, coaches can be identified, etc.). The properties and relationships stored in the ontology can be static, and can be updated periodically (e.g. when players change team).

[0069] The module 208 can extract more dynamic and temporal relationships, by, for example, using text mining and NLP techniques to mine the text documents (i.e. news feeds, blogs, web pages, etc.). For example, given Kobe Bryant, a basketball player of NBA's Los Angeles Lakers, other entities that are related to him in the ontology can be identified, at a given point in time. For example, during the NBA finals, the related entities that can be identified can include his team members, as well as the Lakers' opponent, Boston Celtics, and its top players, such as Kevin Garnett and Ray Allen.

[0070] The ontologies can be populated from multiple structured and semi- structured sources (e.g. Wikipedia). A batch updating process is applied periodically that pulls all the entries from a particular source. Such batch update could also be run by demand on a certain type or group of entities. For example, before major events like Soccer World Cup, we could update all the entities of the facet 'soccer player'. In addition, the system employs an automated and adaptive updating process, by monitoring popular or emerging entities. The goal is that, when a new entity is emerging (e.g. a new musician suddenly becomes very famous, like Susan Boyle), or an entity's popularity rises due to changing property (e.g. sports players are traded to a new team, a person dies, etc.), the system can pull the latest data from the source and update the entity in the ontology in a timely manner.

[0071] The sources of entity that indicate popularity that can be monitored include, by way of example: Frequency counts in our own index of news articles, as well as the timeline (in order to detect emerging entities that have rising popularity); User clicks on entities in a most recent time interval; Wikipedia page view counts (Wikipedia traffic statistics on hourly basis are publicly available from sources such as http://stats. grok.se); Number of most recent mentions in Tweets, through Twitter API; Social networks sites such as Facebook (e.g. Facebook's 'Like' counts); Popular/trending queries from search engines such as Google and Yahoo.

[0072] On a regular time interval (e.g. every hour, every half hour, or every 15 minutes), the system can select a set of top N entities based on a 'Zeitgeist' popularity measure computed by combining the factors listed above. For those identified popular/trending entities, the system can identify the latest data from proper sources, and add new entries or update existing entities' properties in the ontologies immediately. Similarly, the system can compute the Zeitgeist popularity scores on certain categories (i.e. facets) or groups of entities (by aggregating popularity of individual entities that belong to the same group), and update entities by facet or group. [0073] One embodiment of the host server 200 includes a content identifier 210.

The content identifier 210 can be any combination of software agents and/or hardware components able to detect, identify, retrieve, select, content from multiple sources based on a user's topic of interest, an indicia of a user's interest in a topic, and/or topics identified by the server as being related to the user's topic of interest.

[0074] In one embodiment, the content identifier 210 uses a semantic representation of one or more topics to identify content from various sources (e.g., websites, news sites, social networking sites, feeds, etc.). The content that is aggregated can include, news, articles, quotes, comments, video, images, tweets, etc. In one embodiment, the content that is aggregated can be temporally relevant. For example, the server 200 can periodically aggregate content and update the database such that it is identifying up-to-date information for recommendation or presentation to users. In one embodiment, temporally relevant content is identified using the timing module. In some instances, the content identifier 210 has access to location data of the user or the user's device; the location module can then further identify or filter aggregated content that is geographically relevant to the user.

[0075] To identify or pull content, the content identifier module 210 can perform an indexing process, and can support the search of the indexed content using semantic queries. Content can be acquired from news feeds, blog feeds, and by crawling the web. Given a document, the system can apply, for example, text analysis and/or NLP process (i.e. entity tagging and disambiguation) to recognize entities and relationships mentioned in the text.

[0076] Furthermore, the system can link instances of the entity mentions to the corresponding entries in one or more ontolologies and store such semantic annotations of text in an efficient index structure. Thus, the content identifier 210 can retrieve the processed content using entities and/or relationships as queries. Example processes are described in related US Patent No. 7,526,425 entitled "Method and system for extending keyword searching to syntactically and semantically annotated data" and US Patent Application 20090144609 entitled "NLP -based entity recognition and disambiguation", the contents of which are incorporated by reference herein. For content that is exclueded from processing an indexing, the content identifier 210 can use the APIs (e.g., public APIs) to retrieve content (e.g. using YouTube search APIs to retrieve relevant videos). In one embodiment, the identifier 210 uses external APIs to retrieve tweets (e.g, via Twitter search API).

[0077] Content can be pulled periodically (e.g., every 30 sec, every few minutes, every hour, every few hours, every few days, etc.). In one embodiment, content is pulled every few minutes to ensure temporal relevance of the data. Given the pulled or crawled content, the content is added to the indexing pipeline, which can include, applying semantic analysis to identify entities and relationships in the content, hi addition, the indexing process can include storing of the semantic annotations in an efficient indexing structure. Given the semantic representation of user's interest, the system can perform one or more queries against the index, and return a list of content tanked by relevance and timeliness. For content that is being accessed directly via third-party APIs, the semantic representation can be translated by the content identifier 210 into a query form recognizable to the third-party API.

[0078] One embodiment of the host server 200 includes a presentation module 212. The presentation module 212 can be any combination of software agents and/or hardware components able to generate a user interface to present the aggregated content to the user.

[0079] The aggregated content can be presented in a fashion such that the user is able to view and select the content based on topic. For example, if the user indicates interest in 'basketball', and the host server 200 also identifies content related more specifically to the NBA league, Kobe Bryant or the NBA finals, the user interface and provide the content such that the user can select to selectively access content based on topic, for example, as illustrated in the example screenshot of. FIG. 9C. The example of FIG. 9C illustrates that under the 'Oil Spill' collection, the user can select to access content related to 'Barack Obama' or 'BP'.

[0080] One embodiment of the host server 200 includes a mobile platform module

214. The mobile platform module 214 can be any combination of software agents and/or hardware components able to provide an interface of the host server 200 such that it is compatible with a mobile device (e.g., the mobile device in the example of FIG. 3).

[0081] For example, the mobile platform module 214 can adapt the user interface to fit a mobile device screen. In addition, the module 214 adjusts the position and/or form of features (e.g., "follow" button) that the user can use to generate indicia of interest in a topic for easier access. Moreover, mobile devices may be equipped with location sensors which can provide the module 214 with the location data. The module 214 can format or process this data to be used by the host 200 in aggregating or filtering content such that they are also geographically relevant to the user's location.

[0082] Additional or less modules can be included without deviating from the novel art of this disclosure. In addition, each module in the example of FIG. 2 can include any number and combination of sub-modules, and systems, implemented with any combination of hardware and/or software modules.

[0083] The host server 200, although illustrated as comprised of distributed components (physically distributed and/or functionally distributed), could be implemented as a collective element. In some embodiments, some or all of the modules, and/or the functions represented by each of the modules can be combined in any convenient or known manner. Furthermore, the functions represented by the modules can be implemented individually or in any combination thereof, partially or wholly, in hardware, software, or a combination of hardware and software.

[0084] FIG. 3 depicts an example block diagram illustrating the components of a mobile device 300 which is able to manage interest subscriptions for user and also present content (e.g., including temporally-relevant content) to the user based on the subscriptions.

[0085] In one embodiment, mobile device 300 includes a network interface 302, a processing unit 304, a memory unit 306, a storage unit 308, and/or a location sensor 310. Additional or less units or modules may be included.

[0086] The data received from the network interface 302 can be input to the processing unit 304. The processing unit 304 can include one or more processors, CPUs, microcontrollers, FPGAs, ASICs, DSPs, or any combination of the above. Data that is input to the mobile device 300 can be processed by the processing unit 304 and output to a display.

[0087] One embodiment of the mobile device 300 further includes a memory unit

306 and a storage unit 308. The memory unit 306 and a storage unit 308 are, in some embodiments, coupled to the processing unit 304. The memory unit can include volatile and/or non- volatile memory. In one embodiment, the memory unit has stored thereon instructions which when executed by the processor, cause the processor to perform a method for managing interest subscriptions for a user and presenting temporally-relevant content to the user based on the interest subscriptions, for example, by subscribing the user to an interest in response to detecting activation of an indicator via the mobile device, receiving the temporally-relevant content related to multiple topics identified based on the interest subscription via a semantics-enabled platform, and/or displaying the temporally- relevant content via the mobile device, such that the user is able to selectively access the temporally-relevant content identified by the semantics-enabled platform by group.

[0088] FIG. 4 depicts a flow chart illustrating an example process for a mobile device to manage interest subscriptions for a user and to present temporally-relevant content to the user based on the interest subscriptions.

[0089] In process 402, the user is subscribed to an interest in response to detecting activation of an indicator, via a mobile device. In process 404, the interest subscription is managed for the user. In process 406, the temporally-relevant content related to multiple topics identified based on the interest subscription is received via a semantics-enabled platform. The multiple topics can include a topic that is treated as an entity or a relationship in the semantics-enabled platform.

[0090] In process 408, the content is displayed via the mobile device, such that the user is able to selectively access the content identified by the semantics-enabled platform by topic. In one embodiment, the temporally-relevant content is displayed to be categorized based on topic and is selectively accessible to the user by topic. In some cases, the mobile device further includes a location sensor and thus the temporally-relevant content received from the semantics-enabled platform includes content that is also spatially relevant to a location of the mobile device. For example, the content can be filtered for content that is spatially or geographically relevant to the user based on his current location.

[0091] FIG. 5 depicts a flow chart illustrating an example process for using indicia of interest in a topic to identify and aggregate, via a semantics-enabled platform, additional content in which a user is potentially interested.

[0092] In process 502, indicia of interest in a topic are detected. The indicia of interest can be generated by the user via a site hosted by the semantics-enabled platform. The indicia can also be generated by the user via third party sites linked to the semantics enabled platform.

[0093] In process 504, a hierarchy of topics, identified using the topic in which the user is interested, is presented to the user. In process 506, the user is enabled to select from the hierarchy of topics, additional topics of interest, hi process 508, an aggregate group of topics of interest to the user is formed based on the selection. In process 510, the aggregate group of topics of interest to the user is stored in the semantics-enabled platform.

[0094] In process 512, the content from multiple content sources is identified using the semantic representation. The content that is identified or later presented is typically temporally relevant.

[0095] In process 514, the content is presented in an aggregated fashion to the user via a user device, such that the user is able to select content associated with a particular topic of the aggregate group of topics for access. In one embodiment, the content is presented via a site hosted by the semantics-enabled platform, in chronological order; wherein, the content presented on the site includes a link to a full version of the content. The content can be presented via a desktop application, hi one embodiment, a mechanism is provided to share the content for access via a different platform, for example, with other users.

[0096] FIG. 6 depicts a flow chart illustrating an example process for using a semantic representation of a topic to periodically identify content from multiple content sources for presentation to a user.

[0097] In process 602, indicia of interest in a topic are received from a user. The indicia of user interest in the topic, can be generated via activation of a user-perceptible indicator depicted on a website, for example. The indicator can be presented in conjunction with content or with a topic on a website or other data delivery mechanisms. For example, the indicia of user interest in the topic can be received on a website hosted in the semantic platform or on a third party website linked to the semantic platform. Alternatively, the user can generate the indicia from a desktop application or using a mobile device (e.g. using a phone application, the Internet, or via SMS). [0098] In process 604, a semantic representation of the topic in the semantics- enabled platform is generated. In general, the topic can include an entity or a relationship between entities. In one embodiment, a hierarchy of topics is identified using the topic in which the user is potentially interested, for example, using an ontology or taxonomy.

[0099] In process 606, the additional content is periodically identified from multiple content sources (e.g., multiple websites including news sites) using the semantic representation.

[0100] In process 608, the additional content in an aggregated fashion to the user via a user device, such that the user is able to view and select the additional content identified in response to the indicia of user interest in the topic. In process 610, a selection of the multiple topics that are in the collection from the user. In process 612, content is identified from multiple content sources for a collection of multiple topics. In process 614, the thus identified content is presented in an aggregated fashion, such that the user is able to view and select the content in the collection and also such that the user is able to select a subset of the content associated with one of the multiple topics.

[0101] FIG. 7 depicts a flow chart illustrating an example process for using a semantic representation of a topic to periodically identify content from multiple content sources for presentation to a user.

[0102] In process 702, interest of a user in one or more topics is determined based on activation of an indicator associated with a content source. The indicator can be in the form of a clickable button or tab.

[0103] In process 704, the content source (e.g., a web page, search results page, email, feed, status update, voice message, SMS, etc.) is analyzed to identify the one or more topics.

[0104] In process 706, a notification for notifying the user is generated in response to detecting an event associated with the content source and/or identifying other content sources related to the one or more topics. The event can include, one or more of, a notification for notifying the user in response to identifying additional content sources related to the topic of interest. [0105] In process 708, multiple interests of the user are determined based on activation of indicators associated with multiple content sources. One embodiment includes, determining multiple interests of the user based on activation of indicators associated with multiple content sources. In process 710, a notification for notifying the user is generated in response to identifying additional content sources related to the topic of interest.

[0106] FIG. 8A-8C illustrate example screenshots of a site where indicia of interest a topic can be generated by a user.

[0107] The follow button 802 is an example of a mechanism through which a user can generate indicia of interest in a topic (e.g., "FICA World Cup"). In addition, as illustrated in FIG. 8B, the share button 804 can be used to share the content through other sites (e.g., social networking sites). FIG. 8C illustrates how the filter button 806 can be used to select the type of content (e.g., articles, quotes, images, tweets) that the user wants to access.

[0108] FIG. 9A-C illustrates example screenshots showing how a user can generate an indicia of interest and how interests can be tracked and combined to generate interest collections. The example of FIG. 9A shows that the user is FOLLOWING 902 the topic "NBA Finals" (e.g., the user has selected the follow button to indicate interest in the particular topic). FIG. 9B illustrates, for example, under the panel 906, topics that the user is following, or has specified interest in. FIG. 9C illustrates a specific collection of interests created by a user relating to "oil spill". The collection includes several topics each of which can be selected by a user. An example of the list of topics is shown under panel 916 for the collection "oil spill" 914. The user can create a new collection using the button 910.

[0109] FIG. 10 illustrates an example screenshot of content linked to by the host, the content having a panel 1002 through which a user can navigate to related content/topics or return to the host site. The related topics/content depicted in the panel 1002 can be identified and aggregated based on indicia of user interest in a topic. The panel 1002 allows the user to have convenient access to the collection of related content from various sources while accessing content from a third party site. [0110] FIG. 11 illustrates an example screenshot of a third party website having features 1102 through which indicia of interest can be generated by a user for use by a connected semantics-enabled platform (e.g., the host server 100 in the example of FIG. 1) to identify and aggregate additional content to be presented to the user.

[0111] FIG. 12 A-C depict example screenshots showing multiple search results and/or filtered search results which can be "Followed" by a user to generate indicia of interest. Each of the search results can be followed, for example.

[0112] Note that the activation mechanism (e.g., the "Follow" button) can be associated with a search query. In addition, the mechanism can be associated with each individual search result. The examples of FIG. 12 A-C show that the search results can be filtered and each filtered search result can also be individually associated with an activation mechanism. The mechanism through which users can subscribe to content or topics of interest can include multiple indicators (e.g., buttons or other types of selectors) per web page.

[0113] Alternatively, there may be an indicator associated with each content item in the website or webpage. For example, a web page can include one button associated with the main topic of the web page. FIG. 12 A illustrates a screenshot of an example web page with multiple buttons (e.g., the "Follow" button) for use by a user to subscribe to topics/interests through tracking content in the web page. In some instances, the web page includes buttons associated with subtopics. In one embodiment, the web page can include a button associated with each item (e.g., each article, each comment, each posting, each video, each audio track, etc.).

[0114] Note that each interest that is followed can be set to be tracked via a different device, application, and/or mechanism or they can be tracked the same way (e.g., the notifications can be received via the same mechanism and/or the content can be received via the same mechanism. For example, the interests can be tracked via email, SMS, RSS, online message, a call, etc. In addition, each interest can have its own filtering/processing rules or share the same filtering rules.

[0115] By indicating interest through activating the indicator/selector (e.g., a button such as the "Follow" button in the example of FIG. 12A), the user can subscribe to the content source and/or specific topics embodied therein. For example, if the user selects a particular content source (e.g., by activating a selector/indicator), the system can identify various topics included in the piece of content that the user may wish to track. The user may automatically be subscribed to each of the various topics automatically identified in the content source. In some embodiments, the system presents the identified topics and allows the user to select the topics and/or type of content for which the user wishes to receive notifications.

[0116] If the user selects a particular topic (e.g., by indicator activation), the system can identify some topics related to the particular topic for which the user may automatically or selectively subscribe to. In general, in addition to subscribing to topics, users can subscribe to specific terms including but not limited to concepts, keywords, etc. Furthermore, users can subscribe to topics by indicating interests in strings, images, symbols, audio, and/or video content, etc. In one embodiment, interests/topics that users can subscribe to are defined by search queries and/or search queries with filtering rules (e.g., semantic filtering rules, social filtering rules, chronological filtering rules, relevancy filtering rules, other types of filtering rules).

[0117] When the user is subscribed to the content source and/or one or more topics, the system can notify the user about updates/revisions/additions to the content source or "events" associated with the content source. For example, the user can be notified of a revision to the subscribed content source, a new comment/review of the content source, a new file, a new book-mark of the content source, etc. In addition, an event can include, a new search result for a given search query, new articles in a newswire or RSS feed, new email, new mailbox, etc.

[0118] The user can also be alerted about activity of the interest and/or the content source. In addition, the user can be notified or alerted of new or other sources having content that matches or relates to the subscribed topics/interests. The user can be notified via one or more communication mechanisms including but not limited to, an online message, an email, RSS, an SMS text message, a link, an icon, a sound, a web-based reader/application, a desktop reader/application, social networking site, knowledge networking site, Twitter, Facebook, an API, and/or any other form of syndicating notifications, etc. In general, the notifications can be of any length and can include data/content of various levels of detail and various data types. [0119] In some embodiments, the user can be notified of content or new content having topics that are related to the topics of the originally identified content source. For example, if a user has subscribed to a content source related to scuba diving, the system can, in addition to notifying the user about content related to scuba diving, can also notify the user about content related to snorkeling. The scope of the notification may be determined by the source content. In addition, the scope of notification can be modified by the user through the subscription via the content source. For example, the user can narrow or broaden the scope of related topics that they wish to be notified of for a given subscription. The user can also edit the subscription to track additional or different topics or interests.

[0120] FIG. 12D illustrates a screenshot of an example of a pop-up screen that allows the user to specify the topic/interest to subscribe to, in response to receiving indicia of user interest in a topic or content. For example, when a user activates a selector/indicator (e.g., the "Follow" button) associated with a search result or content entry, the pop-up screen may automatically be depicted to allow the user to select the topics/interests to subscribe to (e.g., check the topics/interests to subscribe to and click "Follow"). Multiple options can be presented to the user. In general, the options presented to the user are selected using content extracted from the page or link associated with the activated selector (e.g., button). The user can also indicate that none of the presented options are of interest and to not subscribe (click "No Thanks") to any of the topics/interests.

[0121] FIG. 13 depicts another example of a third-party web page having content that can be tracked by a user using associated features/mechanisms (e.g., the "Follow" buttons 1304).

[0122] FIG. 14 illustrates a screenshot of an example web interface for accessing a tracking agent which can be used to manage subscribed topics/interests and to view/browse the content associated with the subscription. The follow buttons can be used to indicate interest in a topic, article, or piece of content.

[0123] In one aspect, the present disclosure relates to a tracker for a user to manage and/or access the topics/interests subscribed to by a user. The tracker can be accessible via a web interface through a web browser. The tracker may also be accessible through a desktop application to manage the notifications and/or track content that is both online and/or offline.

[0124] The tracker can also allow the user to manage the notifications/interests and/or associated content from different websites and/or applications. A user can thus use the tracker to view/browse the subscribed topics/interests and the associated content/notifications. In one embodiment, the tracker can be used to sort the associate content/notifications by various interests. For example, the user can select to view the content/notifications associated with specific interests in the tracker. In addition, the tracker can be used by the user to search within the collection of content matching the user's interest/topic subscriptions or to search within the content matching a particular interest/topic subscription.

[0125] In one embodiment, the tracker sends out notifications or enables notifications to be retrieved by request of the user or an application. For example, a user can access notifications and/or the associated content through an external application (e.g., email, RSS, API of a social networking site including but not limited to Twitter, Facebook, etc., API of a knowledge networking site, Short Messaging Services, etc.) using the tracker.

[0126] FIG. 15A-E depict screenshots of user interfaces on a mobile device showing features (e.g., "FOLLOW" button) allowing users to generate indicia of interest for topics (e.g., channels) and content.

[0127] FIG. 16 shows a diagrammatic representation of a machine in the example form of a computer system 1600 within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.

[0128] In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. [0129] The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a laptop computer, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, an iPhone, a Blackberry, a processor, a telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.

[0130] While the machine-readable medium or machine-readable storage medium is shown in an exemplary embodiment to be a single medium, the term "machine-readable medium" and "machine-readable storage medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term "machine- readable medium" and "machine-readable storage medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the presently disclosed technique and innovation.

[0131] In general, the routines executed to implement the embodiments of the disclosure, may be implemented as part of an operating system or a specific application, component, program, object, module or sequence of instructions referred to as "computer programs." The computer programs typically comprise one or more instructions set at various times in various memory and storage devices in a computer, and that, when read and executed by one or more processing units or processors in a computer, cause the computer to perform operations to execute elements involving the various aspects of the disclosure.

[0132] Moreover, while embodiments have been described in the context of fully functioning computers and computer systems, those skilled in the art will appreciate that the various embodiments are capable of being distributed as a program product in a variety of forms, and that the disclosure applies equally regardless of the particular type of machine or computer-readable media used to actually effect the distribution.

[0133] Further examples of machine-readable storage media, machine-readable media, or computer-readable (storage) media include but are not limited to recordable type media such as volatile and non-volatile memory devices, floppy and other removable disks, hard disk drives, optical disks (e.g., Compact Disk Read-Only Memory (CD ROMS), Digital Versatile Disks, (DVDs), etc.), among others, and transmission type media such as digital and analog communication links.

[0134] Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise," "comprising," and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of "including, but not limited to." As used herein, the terms "connected," "coupled," or any variant thereof, means any connection or coupling, either direct or indirect, between two or more elements; the coupling of connection between the elements can be physical, logical, or a combination thereof.

[0135] Additionally, the words "herein," "above," "below," and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word "or," in reference to a list of two or more items, covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list.

[0136] The above detailed description of embodiments of the disclosure is not intended to be exhaustive or to limit the teachings to the precise form disclosed above. While specific embodiments of, and examples for, the disclosure are described above for illustrative purposes, various equivalent modifications are possible within the scope of the disclosure, as those skilled in the relevant art will recognize. For example, while processes or blocks are presented in a given order, alternative embodiments may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified to provide alternative or subcombinations. Each of these processes or blocks may be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed in parallel, or may be performed at different times. Further any specific numbers noted herein are only examples: alternative implementations may employ differing values or ranges.

[0137] The teachings of the disclosure provided herein can be applied to other systems, not necessarily the system described above. The elements and acts of the various embodiments described above can be combined to provide further embodiments. [0138] Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the disclosure can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further embodiments of the disclosure.

[0139] These and other changes can be made to the disclosure in light of the above

Detailed Description. While the above description describes certain embodiments of the disclosure, and describes the best mode contemplated, no matter how detailed the above appears in text, the teachings can be practiced in many ways. Details of the system may vary considerably in its implementation details, while still being encompassed by the subject matter disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the disclosure should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the disclosure with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the disclosure to the specific embodiments disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the disclosure encompasses not only the disclosed embodiments, but also all equivalent ways of practicing or implementing the disclosure under the claims.

[0140] While certain aspects of the disclosure are presented below in certain claim forms, the inventors contemplate the various aspects of the disclosure in any number of claim forms. For example, while only one aspect of the disclosure is recited as a means- plus-function claim under 35 U. S. C. §112, IJl 3, other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer- readable medium. (Any claims intended to be treated under 35 U. S. C. §112, f 13 will begin with the words "means for".) Accordingly, the applicant reserves the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the disclosure.

Claims

ClaimsWhat is claimed is:

1. A method for using indicia of interest in a topic to identify and aggregate, via a semantics-enabled platform, content in which a user is potentially interested, comprising: presenting, to the user, a hierarchy of topics identified using the topic in which the user is interested; enabling the user to select from the hierarchy of topics, additional topics of interest and forming an aggregate group of topics of interest to the user based on the selection; storing the aggregate group of topics of interest to the user in the semantics- enabled platform; identifying the content from multiple content sources using the semantic representation; presenting the content in an aggregated fashion to the user via a user device, such that the user is able to select content associated with a particular topic of the aggregate group of topics for access.

2. The method of claim 1 , further comprising, providing a mechanism to share the content for access via a different platform.

3. The method of claim 1 , wherein, the content is temporally relevant.

4. The method of claim 1 , wherein, the content is presented via a site hosted by the semantics-enabled platform, in chronological order; wherein, the content presented on the site includes a link to an expanded version of the content.

5. The method of claim 1 , wherein, the content is presented via a desktop application.

6. The method of claim 1 , wherein, the indicia of interest is generated by the user via a site hosted by the semantics-enabled platform.

7. The method of claim 1 , wherein, the hierarchy of topics are identified using a hierarchical taxonomy using facets of a semantic entity that represents the topic.

8. The method of claim 1 , wherein, the hierarchy of topics are identified using properties of a semantic entity that represents the topic.

9. The method of claim 1 , wherein, the hierarchy of topics is identified by traversing relationship links of a semantic entity that represents the topic.

10. The method of claim 1 , further comprising, representing the topic as a semantic object associated with an entity or relationship; wherein, the semantic object has associated properties and relationships; updating the associated properties and relationships to the semantic object.

11. The method of claim 1 , wherein, the topic is represented a semantic object having dynamic properties.

12. The method of claim 11 , further comprising, mining a text document related to the topic to identify the dynamic properties; using the dynamic properties to identify the hierarchy of topics.

13. The method of claim 1, wherein, the topic is represented a semantic object having dynamic relationships.

14. The method of claim 13 , further comprising, mining a text document related to the topic to identify the dynamic relationships; using the dynamic relationships to identify the hierarchy of topics.

15. A method for using an indicia of interest in a topic to identify and aggregate content in which a user is potentially interested, comprising: generating a semantic representation of the topic; periodically identifying the content from multiple content sources using the semantic representation; presenting the content in an aggregated fashion to the user via a user device, such that the user is able to view and select the content identified in response to the indicia of user interest in the topic.

16. The method of claim 15, wherein, the multiple content sources include websites; wherein, the websites include news sites.

17. The method of claim 15, wherein, the content includes, one or more of, images, articles, feed, and blogs.

18. The method of claim 15, wherein, the content includes, quotes.

19. The method of claim 15, wherein, the content includes, tweets.

20. The method of claim 15, further comprising, identifying a hierarchy of topics using the topic in which the user is potentially interested.

21. The method of claim 20, wherein, the hierarchy of topics are identified using an ontology or taxonomy.

22. The method of claim 15, wherein, the topic includes an entity.

23. The method of claim 15, wherein, the topic includes a relationship between entities.

24. The method of claim 15, wherein, the indicia of user interest in the topic, is generated via activation of a user-perceptible indicator depicted on a website.

25. The method of claim 24, wherein, the user-perceptible indicator is presented in conjunction with content.

26. The method of claim 24, wherein, the user-perceptible indicator is presented in conjunction with a topic.

27. The method of claim 15, wherein, the indicia of user interest in the topic is received on a website hosted in the semantic platform.

28. The method of claim 15, wherein, the indicia of user interest in the topic is received on a third party website linked to the semantic platform.

29. The method of claim 15, wherein, the user generates the indicia of user interest from a desktop application.

30. The method of claim 15, wherein, the user generates the indicia of user interest from a mobile device.

31. The method of claim 15, further comprising: further identifying content from multiple content sources for a collection of multiple topics; presenting the thus identified content in an aggregated fashion, such that the user is able to view and select the content in the collection and also such that the user is able to select a subset of the content associated with one of the multiple topics.

32. The method of claim 31 , further comprising, receiving a selection of the multiple topics that are in the collection from the user.

33. The method of claim 15, further comprising, semantically analyzing the content from the multiple sources to identify entities and relationships in the content; generating an index for the content based on the entities and the relationships.

34. The method of claim 33, further comprising, querying the index to identify the content to be presented to the user; wherein, the query returns results based on topical relevance and temporal relevance.

35. A mobile device, comprising: a processor; a memory unit coupled to the processor, the memory having stored thereon instructions which when executed by the processor, cause the processor to perform a method for managing interest subscriptions for a user and presenting temporally- relevant content to the user based on the interest subscriptions, the method, comprising: subscribing the user to an interest in response to detecting activation of an indicator via the mobile device; receiving the temporally-relevant content related to multiple topics identified based on the interest subscription via a semantics-enabled platform; displaying the temporally-relevant content via the mobile device, such that the user is able to selectively access the temporally-relevant content identified by the semantics-enabled platform by group.

36. The mobile device of claim 35, wherein, the temporally-relevant content is displayed to be categorized based on topic and is selectively accessible to the user by topic.

37. The mobile device of claim 35, further comprising: a location sensor; wherein, the temporally-relevant content received from the semantics- enabled platform includes content that is also spatially relevant to a location of the mobile device.

38. The mobile device of claim 35, wherein, the multiple topics includes a topic that is treated as an entity in the semantics-enabled platform.

39. The mobile device of claim 35, wherein, the multiple topics includes a topic that is treated as a relationship in the semantics-enabled platform.

40. A machine-readable storage medium having stored thereon a set of instructions which when executed causes a processor to perform a method, comprising: determining interest of a user in one or more topics based on activation of an indicator associated with a content source; analyzing the content source to identify the one or more topics; and generating a notification for notifying the user in response to detecting an event associated with the content source and/or identifying other content sources related to the one or more topics.

41. The method of claim 40, wherein, the event includes, one or more of, a revision, a comment, a review, a bookmark, and a tagging event.

42. The method of claim 40, wherein, the content source is a web page.

43. The method of claim 40, further comprising, determining multiple interests of the user based on activation of indicators associated with multiple content sources.

44. The method of claim 43, further comprising, tracking notifications and multiple content sources for each of the multiple interests for the user.

45. The method of claim 40, wherein, the indicator is in the form of a clickable button or tab.

46. The method of claim 40, wherein, the content source is a search results page;

47. The method of claim 46, wherein, the search results page includes multiple indicators each associated with a search result.

48. The method of claim 46, further comprising, generating a notification for notifying the user in response to identifying additional content sources related to the topic of interest.