ABSTRACT: Accounting language evolves as the transactions and organizations it provides guidance for change. We provide a preliminary analysis of terms used in official accounting pronouncements and annual corporate financial statements. Initial results show statistical natural language-processing techniques provide a means of identifying new terms as they enter the lexicon. These techniques should be valuable in deriving a complete accounting lexicon as well as in constructing and maintaining an accounting thesaurus to support information retrieval.
AbstractDefinitions are provided of the key entities in knowledge representation for Natural Language Processing (NLP). Starting from the words, which are the natural components of any sentence, both the role of expressions and the decomposition of words into their parts are emphasized. This leads to the notion of concepts, which are either primitive or composite depending on the model where they are created. The problem of finding the most adequate degree of granularity for a concept is studied. From this reflection on basic Natural Language Processing components, four categories of linguistic knowledge are recognized, that are considered to be the building blocks of a Medical Linguistic Knowledge Base (MLKB). Following on the tracks of a recent experience in building a natural language-based patient encoding browser, a robust method for conceptual indexing and query of medical texts is presented with particular attention to the scheme of knowledge representation.
Foundations of Statistical Natural Language Processing Christopher D. Manning and Hinrich Schütze (Stanford University and Xerox Palo Alto Research Center) Cambridge, MA: The MIT Press, 1999, xxxvii + 680 pp; hardbound, ISBN 0-262-13360-1, $60.00