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Fabienne Moreau, Vincent Claveau,
Extension
de requêtes par relations morphologiques apprises automatiquement,
Actes de la 3ème COnférence en Recherche d'Information et Applications
(CORIA'06), Lyon,
France, mars 2006,
Document
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Abstract Information
retrieval systems (IRS) usually suffer from a low ability to recognize
a same idea or concept that is expressed in different forms. A way of
improving these systems is to take into account morphological
variations. In this paper, we propose a simple method to recognize
these variations that are further used so as to enrich queries. In
comparison with already published methods, this system does not need an
external ressources or knowledge and thus supports many languages. This
approach is evaluated on several collections, 6 different languages and
compared to existing tools (stemmer, lemmatizer); reported results show
a significant improvement of the overall IRS performance in every case.
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