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 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 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 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 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 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: 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: 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: Computer implemented methods for identifying denial constraints are provided herein. The denial constraints can be used with a database schema R. A predicate space P can be generated for an instance I in the schema R. An evidence set EviI can be generated. The evidence set EviI can include sets of satisfied predicates in the predicate space P for each instance I. A minimal set of predicates can be identified for the evidence set EviI. Valid denial constraints can be identified from the minimal set by inverting the predicates in the minimal set.

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 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: A system for checking data for errors, the system comprising a checking module operable to check tuples of data stored in a target database for errors, the tuples in the target database originating from the output of at least one query transformation module which applies a query transformation to tuples of data from at least one data source an identification module operable to identify a problematic tuple from a data source that produces an error in the target database, the identification module being operable to quantify the contribution of the problematic tuple in producing the error in the target database, and a description generation module operable to generate a descriptive query which represents at least one of errors identified by the checking module in the target database which are produced by the at least one query transformation module, and problematic tuples identified in a data source by the identification module.

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: 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: 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.