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L. Alfonso Ureña ; M. Teresa Martín ;Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial 2004, 8 (22)

Autor: Fernando Martínez

Fuente: http://www.redalyc.org/


Introducción



Inteligencia Artificial.
Revista Iberoamericana de Inteligencia Artificial ISSN: 1137-3601 revista@aepia.org Asociación Española para la Inteligencia Artificial España Martínez, Fernando; Ureña, L.
Alfonso; Martín, M.
Teresa SINAI experience at CLEF Inteligencia Artificial.
Revista Iberoamericana de Inteligencia Artificial, vol.
8, núm.
22, primavera, 2004, pp.
111-121 Asociación Española para la Inteligencia Artificial Valencia, España Available in: http:--www.redalyc.org-articulo.oa?id=92582208 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative SINAI experience at CLEF Fernando Martı́nez, L.
Alfonso Ureña, M.
Teresa Martı́n Dpto.
Informática.
Universidad de Jaén Av.
Madrid, 35 Jaén, E-23071 Spain {dofer,laurena,maite}@ujaen.es Abstract This paper reports our work on CLEF and CrossLanguage Information Retrieval using CLEF resources.
We aim to construct a highly languageindependent CLIR model.
To accomplish this objective, several problems must be overcome: text translation or pseudo-translation and merging the obtained results for each language for a given query.
Three issues of text-translation are investigated: the impact of translation probabilities, automatic multi-word recognition, and the generation of similarity thesauri from a Web corpus. Because the proposed model is query-translation driven, it is necessary to merge several monolingual results in a unique multilingual list of documents.
To accomplish this task, we propose a new approach, which we call 2-step RSV, and we show that it performs better than more traditional approaches. Keywords: Cross-Lingual Information Retrieval, Retrieved Status Value, Merging strategies, Multi-word, Similarity thesaurus. 1 Introduction The typical CLIR requiremen...





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