Abstract: Systems and methods are provided for non-monotonic recognition of phrasal terms. Phrasal terms are identified from a corpus of written materials and ranked based on, for example, a mutual rank ratio. The phrasal terms are sequentially selected and a determination is made as to whether to accept or reject the selected phrasal term based on at least one predetermined criteria. The ranking of the phrasal terms may also rely on linguistic support to reduce duplication of phrasal terms and to distinguish different confidence levels for identified and accepted phrasal terms.

Abstract: Systems and methods are provided for non-monotonic recognition of phrasal terms. Phrasal terms are identified from a corpus of written materials and ranked based on, for example, a mutual rank ratio. The phrasal terms are sequentially selected and a determination is made as to whether to accept or reject the selected phrasal term based on at least one predetermined criteria. The ranking of the phrasal terms may also rely on linguistic support to reduce duplication of phrasal terms and to distinguish different confidence levels for identified and accepted phrasal terms.

Abstract: Systems and methods are disclosed for analyzing a set of documents by building a positive set histogram; selecting phrases from the positive set histogram; modifying the frequency statistics in the histogram using the selected phrases; identifying one or more potential phrase-acronym pairs; selecting a subset of phrase-acronym pairs from the potential pairs; adding a new feature for each selected phrase-acronym (phrase ? acronym) pair to a positive set histogram; determining a value for each new feature; identifying one or more child concepts based on an updated histogram; grouping the one or more child concepts; and determining a child concept group coverage for one or more documents.