Integrating a Lexical Database and a Training Collection for Text Categorization

dc.creatorHidalgo, Jose Maria Gomez
dc.creatorRodriguez, Manuel de Buenaga
dc.date1997-09-15
dc.date.accessioned2026-07-07T09:10:58Z
dc.date.available2026-07-07T09:10:58Z
dc.descriptionAutomatic text categorization is a complex and useful task for many natural language processing applications. Recent approaches to text categorization focus more on algorithms than on resources involved in this operation. In contrast to this trend, we present an approach based on the integration of widely available resources as lexical databases and training collections to overcome current limitations of the task. Our approach makes use of WordNet synonymy information to increase evidence for bad trained categories. When testing a direct categorization, a WordNet based one, a training algorithm, and our integrated approach, the latter exhibits a better perfomance than any of the others. Incidentally, WordNet based approach perfomance is comparable with the training approach one.
dc.description12 pages, 3 figures (2 tables)
dc.identifierhttps://arxiv.org/abs/cmp-lg/9709004
dc.identifierhttp://arxiv.org/abs/cmp-lg/9709004
dc.identifierACL/EACL Workshop on Automatic Extraction and Building of Lexical Semantic Resources for Natural Language Applications, 1997
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151520
dc.subjectComputation and Language
dc.titleIntegrating a Lexical Database and a Training Collection for Text Categorization
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