Abstract: A method includes analyzing a cluster of conceptually-related portions of text to develop a model and calculating a novelty measurement between a first identified conceptually-related portion of text and the model. The method further includes transmitting a second identified conceptually-related portion of text and a score associated with the novelty measurement from a server to an access device via a signal. Another method includes determining at least two corpora of conceptually-related portions of text. The method also includes calculating a common neighbors similarity measurement between the at least two corpora of conceptually-related portions of text and if the common neighbors similarity measurement exceeds a threshold, merging the at least two corpora of conceptually-related portions of text into a cluster or if the common neighbors similarity measurement does not exceed a threshold, maintaining a non-merge of the at least two corpora of conceptually-related portions of text.

Abstract: A method includes analyzing a cluster of conceptually-related portions of text to develop a model and calculating a novelty measurement between a first identified conceptually-related portion of text and the model. The method further includes transmitting a second identified conceptually-related portion of text and a score associated with the novelty measurement from a server to an access device via a signal. Another method includes determining at least two corpora of conceptually-related portions of text. The method also includes calculating a common neighbors similarity measurement between the at least two corpora of conceptually-related portions of text and if the common neighbors similarity measurement exceeds a threshold, merging the at least two corpora of conceptually-related portions of text into a cluster or if the common neighbors similarity measurement does not exceed a threshold, maintaining a non-merge of the at least two corpora of conceptually-related portions of text.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.