Abstract: According to one embodiment of the disclosure, a query generation system generally includes an element rank and inference engine in communication with a computing system and a user interface. The element rank and inference engine is operable to receive a user supplied element from the user interface, the user supplied element being associated with a first filter criterion. The element rank and inference engine is also operable to create, using the first filter criterion, at least one second element and rank according to their relative importance, the at least one first element and the at least one second element according to their associated first filter criterion and second filter criterion. Next, the element rank and inference engine may output the at least one first filter element and the second filter element to the computing system.

Abstract: A method includes determining a plurality of social objects, each social object having a link to a link object on a network. The method further includes applying a filter to the determined social objects in order to determine a plurality of filtered social objects, retrieving a copy of each of the link objects linked to by the plurality of filtered social objects, and generating, using the retrieved copies of the link objects linked to by the plurality of filtered social objects, a matrix comprising a plurality of vectors. The method further includes generating a singular value representation of the matrix by performing Singular Value Decomposition (SVD) on the matrix and storing the singular value representation of the matrix in one or more memory units.

Abstract: According to one embodiment of the disclosure, a query generation system generally includes an element rank and inference engine in communication with a computing system and a user interface. The element rank and inference engine is operable to receive a user supplied element from the user interface, the user supplied element being associated with a first filter criterion. The element rank and inference engine is also operable to create, using the first filter criterion, at least one second element and rank according to their relative importance, the at least one first element and the at least one second element according to their associated first filter criterion and second filter criterion. Next, the element rank and inference engine may output the at least one first filter element and the second filter element to the computing system.

Abstract: A method includes determining a plurality of social objects, each social object having a link to a link object on a network. The method further includes applying a filter to the determined social objects in order to determine a plurality of filtered social objects, retrieving a copy of each of the link objects linked to by the plurality of filtered social objects, and generating, using the retrieved copies of the link objects linked to by the plurality of filtered social objects, a matrix comprising a plurality of vectors. The method further includes generating a singular value representation of the matrix by performing Singular Value Decomposition (SVD) on the matrix and storing the singular value representation of the matrix in one or more memory units.

Abstract: According to one embodiment of the disclosure, a query generation system generally includes an element rank and inference engine in communication with a computing system and a user interface. The element rank and inference engine is operable to receive a user supplied element from the user interface, the user supplied element being associated with a first filter criterion. The element rank and inference engine is also operable to create, using the first filter criterion, at least one second element and rank according to their relative importance, the at least one first element and the at least one second element according to their associated first filter criterion and second filter criterion. Next, the element rank and inference engine may output the at least one first filter element and the second filter element to the computing system.

Abstract: A method includes accessing text, identifying a plurality of terms from the text, determining a plurality of term vectors associated with the identified plurality of terms, and clustering the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first and a second cluster, the first and second clusters each comprising two or more of the determined term vectors. The method further includes creating a first pseudo-document according to the first cluster, creating a second pseudo-document according to the second cluster, identifying a first set of terms associated with the first cluster using latent semantic analysis (LSA) of the first pseudo-document, identifying a second set of terms associated with the second cluster using LSA of the second pseudo-document, and combining the first and second sets of terms into a list of output terms.

Abstract: A method includes accessing text, identifying a plurality of terms from the text, determining a plurality of term vectors associated with the identified plurality of terms, and clustering the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first and a second cluster, the first and second clusters each comprising two or more of the determined term vectors. The method further includes creating a first pseudo-document according to the first cluster, creating a second pseudo-document according to the second cluster, identifying a first set of terms associated with the first cluster using latent semantic analysis (LSA) of the first pseudo-document, identifying a second set of terms associated with the second cluster using LSA of the second pseudo-document, and combining the first and second sets of terms into a list of output terms.

Abstract: A method includes accessing text that includes a plurality of words, tagging each of the plurality of words with one of a plurality of parts of speech (POS) tags, and creating a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag. The method further includes clustering one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens, and forming a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens.