1. A method for automated learning of terminology from an input set of documents, the method comprising the steps of: storing a classification system comprising a plurality of categories of terminology arranged to reflect associations among related categories; processing the input set of documents to classify each of the documents into a category of the classification system, wherein the documents classified contain a term for learning; generating contextual data for the term for learning by mapping the categories selected to the classification system so as reflect associations among the categories selected; analyzing the contextual data, including analyzing all of the categories selected in the classification system for the term, prior to selecting a single category for the term; and selecting a single category, based on the associations of the categories in the classification system, for the term to learn the term as the single category.
1. A method for automated learning of terminology from an input set of documents, the method comprising the steps of: storing a classification system comprising a plurality of categories of terminology arranged to reflect associations among related categories; processing the input set of documents to classify each of the documents into a category of the classification system, wherein the documents classified contain a term for learning; generating contextual data for the term for learning by mapping the categories selected to the classification system so as reflect associations among the categories selected; analyzing the contextual data, including analyzing all of the categories selected in the classification system for the term, prior to selecting a single category for the term; and selecting a single category, based on the associations of the categories in the classification system, for the term to learn the term as the single category. 2. The method as set forth in claim 1, wherein the step of analyzing the contextual data comprises the steps of: determining whether the term is ambiguous such that the contextual data for the term does not indicate selection of a single category; and removing the term from consideration for learning if the term is ambiguous.