Abstract: Techniques for presenting content to users. The techniques include: obtaining user context information including a first keyword; identifying, based on the first keyword, a first attribute and a second attribute among the plurality of attributes, the first attribute being a characteristic of the first keyword and the second attribute being another characteristic of the first keyword; obtaining, based on the user context information, at least one second-order user preference among attributes in the plurality of attributes including a preference between the first attribute and the second attribute; identifying a set of content items among the plurality of content items based on the first attribute and the second attribute; determining a ranking of content items in the set of content items based on the at least one second-order user preference; and presenting content items to the user in accordance with the ranking.

Abstract: This invention relates generally to classification systems. More particularly this invention relates to a system, method, and computer program to dynamically generate a domain of information synthesized by a classification system or semantic network. The invention discloses a method, system, and computer program providing a means by which an information store comprised of knowledge representations, such as a web site comprised of a plurality of web pages or a database comprised of a plurality of data instances, may be optimally organized and accessed based on relational links between ideas defined by one or more thoughts identified by an agent and one or more ideas embodied by the data instances. Such means is hereinafter referred to as a “thought network”.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Systems and methods are provided for generating training data for a machine-learning classifier. A knowledge representation synthesized based on an object of interest is used to assign labels to content items. The labeled content items can be used as training data for training a machine learning classifier. The labeled content items can also be used as validation data for the classifier.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Disclosed is a system and method for enhancing value for advertisers by helping them select and initiate the purchase of an advertisement associated with an advertising (ad) words or phrases that have strong semantic relationships to a given context, but which are not necessarily the most popular ad words or phrases with the highest costs. Advertisements associated with ad words or phrases that have strong semantic relationships to a given context, and yet are still cost effective in that their calculated value exceeds the costs of purchasing the ad keywords, are bid for and bought. In an embodiment, the system and method may be adapted to automatically purchase advertisements associated with ad words or phrases when the ad words or phrases fall within a desired price range based on their calculated value.

Abstract: A method of semantic searching. The method may include receiving a first search query, obtaining a disambiguation term for semantically disambiguating the first search query, and creating, with a processor, a second search query based at least in part on the first search query and the disambiguation term. The method may also include at least one of outputting search results obtained from a search conducted based at least in part on the second search query and sending the second search query to a search service for outputting search results.

Abstract: There is disclosed a system and method for using a knowledge representation to provide relevant information based on environmental inputs. In an embodiment, the system and method considers environmental information from members in a crowd to generate a pool of interests based on the semantic relevance concepts associated with those interests. The most prominent concepts of interest may then be the basis for presenting content to the crowd as a whole. In another embodiment, environmental inputs and other surrounding inputs are considered as a user context. The concepts may be identified as relevant from the environmental context and used to present information relevant to the user given his or her surroundings.

Abstract: Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Abstract: Techniques for use in identifying one or more concepts in a knowledge representation (KR). The techniques include obtaining user context information associated with a user, wherein the user context information comprises a plurality of words; Also included are semantic disambiguation techniques comprising obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first and second concept in a knowledge representation (KR) associated with a first meaning of the first portion. Semantic disambiguation techniques further include obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept and second concept in a knowledge representation (KR) using a measures of dominance and semantic coherence.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Techniques for presenting content to users. The techniques include: obtaining user context information including a first keyword; identifying, based on the first keyword, a first attribute and a second attribute among the plurality of attributes, the first attribute being a characteristic of the first keyword and the second attribute being another characteristic of the first keyword; obtaining, based on the user context information, at least one second-order user preference among attributes in the plurality of attributes including a preference between the first attribute and the second attribute; identifying a set of content items among the plurality of content items based on the first attribute and the second attribute; determining a ranking of content items in the set of content items based on the at least one second-order user preference; and presenting content items to the user in accordance with the ranking.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may depend on user models, context information, preference information, and/or preference models.

Abstract: Disclosed is a system and method for performing a semantic operation on a social network. In an embodiment, the method comprises receiving a social network user context associated with a user of the social network; generating, through a semantic operation, an interest network based on the user context information; and filtering, ranking or augmenting, using at least one processor executing stored program instructions, a retrieval of information related to the social network based on the interest network; wherein the interest network comprises concepts represented by a data structure associated with the concepts in the interest network. In another embodiment, the method further comprises representing the interest network as an interest graph. In yet another embodiment, the semantic operation is a synthesis operation or retrieval operation performed on a knowledge representation.

Abstract: The present invention provides a computer network implementable integration of promoted information with non-promoted content before a consumer interaction with the network, such that when the consumer interacts with the network, a consumer information interacts with this integrated content and delivers a message to the consumer such that the consumer visualizes this message as part of consumer experience without distracting from the network interaction task at hand. The integration is facilitated by semantic analysis and synthesis to naturally position the promoted content as close to the consumer interaction tasks as possible at that instant. This approach displaces the current practise of matching message to media placement while further enabling a promoter to evaluate and respond to feedback data depicting the efficacy of the sponsor message. The network in question is any computer network such as the Internet or intranet.

Abstract: A computer network-implemented method for displaying a tag cloud representing a data structure. The data structure includes data entities and representations of relationships between the data entities. The method enables one or more users to interact with the data structure, and via the data structure, to interact with one another. In an example embodiment, the method comprises, via a computer processor, populating a display of a user interface showing a tag cloud populated with images of data entities from the data structure, such images, and in response to user input to the interface, associating one or more visual properties of the user interface with one or more of said relationships between data entities in the data structure.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing complex KRs from the elemental data structure may rely on linguistic inference rules and/or elemental inference rules.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with an input context. Multiple input complex KRs of various types may be analyzed and deconstructed to populate the elemental data structure, and input complex KRs may be transformed through the elemental data structure to output complex KRs of different types, providing semantic interoperability to KRs of different types and/or KR models.

Abstract: Techniques are described for performing synthesis of relationships between a plurality of concept definitions automatically derived from a faceted domain of information. Some embodiments involve identifying at least one facet attribute in an active concept definition specified by user input. In response to determining that at least one explicit relationship and/or at least one implicit relationship exist(s) between the active concept definition and a first concept definition of the plurality of concept definitions, a relationship is synthesized between the active concept definition and the first concept definition.

Abstract: Methods and system for providing information selected from a large set of digital content to at least one user. One such method comprises receiving user context information associated with the at least one user and identifying or generating, using at least one processor executing stored program instructions, a first concept in a semantic network, the first concept representing at least a portion of the user context information.