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: 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 use in identifying one of 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.