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PubMed · 9357693

Corpus-based identification and refinement of semantic classes.

A Nazarenko·P Zweigenbaum·J Bouaud·B Habert
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Abstract

Medical Language Processing (MLP), especially in specific domains, requires fine-grained semantic lexica. We examine whether robust natural language processing tools used on a representative corpus of a domain help in building and refining a semantic categorization. We test this hypothesis with ZELLIG, a corpus analysis tool. The first clusters we obtain are consistent with a model of the domain, as found in the SNOMED nomenclature. They correspond to coarse-grained semantic categories, but isolate as well lexical idiosyncrasies belonging to the clinical sub-language. Moreover, they help categorize additional words.

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ClassificationLinguisticsNatural Language ProcessingSemanticsVocabulary, ControlledJournal Article

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A Nazarenko, P Zweigenbaum, J Bouaud, B Habert. 1997. Corpus-based identification and refinement of semantic classes.. https://pubmed.ncbi.nlm.nih.gov/9357693/

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