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 for specifying user preferences in a semantic network. The techniques include receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user's preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user's preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

Abstract: Methods and system of searching for content in a target set of content based on a reference set of content, a reference semantic network representing knowledge associated with the reference set of content, and a target semantic network representing knowledge associated with the target set of content. Techniques include receiving a user-specified search query, obtaining at least one concept semantically relevant to the user-specified search query by using the target semantic network and the reference semantic network, constructing a second query by augmenting the first search query with one or more terms associated with the at least one obtained concept; providing, to the at least one user, content associated with search results obtained based on searching the target set of content by using the second query, wherein any concept in the semantic network is represented by a data structure storing data associated with a node in the semantic 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: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively. A method of constructing an elemental data structure may include analyzing first information to identify a first elemental component associated with a data consumer, and adding the first elemental component to a customized module corresponding to the data consumer. The method may also include analyzing second information to identify a second elemental component associated with a population, and adding the second elemental component to the universal kernel.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. The elemental data structure may include a universal kernel and one or more customized modules. The universal kernel may represent knowledge that is generally applicable to a population, and the customized modules may represent knowledge that is specifically applicable to individual data consumers. Crowd-sourcing techniques may be applied to the elemental data structure. A method of modifying the elemental data structure may include obtaining an indicator regarding an elemental component based on data associated with customized modules.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively. A method of outputting a complex KR may include receiving input from a data consumer. The method may further include applying rules to the elemental data structure. Applying rules to the elemental data structure may include applying a rule to the universal kernel and applying a rule to a customized module. The method may further include synthesizing a concept and/or a relationship based on the application of the rules, and outputting a complex KR that is customized to the data consumer based on the customized module.

Abstract: Techniques for specifying user preferences in a semantic network. The techniques include receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user's preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user's preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

Abstract: The present invention relates to a system, method and computer program for creating, visualizing and manipulating a data structure using an intuitive and interactive graphical interface. It is operable to display a data structure and enable users to interact with the data structure by means of a user interface. The data structure includes data entities and relationships between the data entities. One or more user context properties are associable with the data entities. The user interface is populated with data entities from the data structure by enabling the users to associate visual properties of the user interface with the user context associable properties of the data structure. This enables the users to interact with the data structure by means of the user interface.

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 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: 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.

Abstract: Methods and system of searching for content in a target set of content based on a reference set of content, a reference semantic network representing knowledge associated with the reference set of content, and a target semantic network representing knowledge associated with the target set of content.

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: 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.