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RESUME. Ce papier presente une approche multi-vue pour la traduction de termes de special-ite, basee sur un lexique bilingue et un corpus comparable. Nous proposons d'etudier dif-ferents niveaux de representation pour un terme : le contexte, le theme et la graphie. Ces trois approches sont tout d'abord etudiees individuellement, puis combinees afin de selection-ner les meilleures traductions. Des experiences menees sur la traduction de termes medicaux du francais vers l'anglais montrent une amelioration de l'approche classique par contexte, at-teignant une precision de 80,4% de bonnes traductions au rang 1. ABSTRACT. This paper presents a multi-view approach for term translation spotting, based on a bilingual lexicon and comparable corpora. We propose to study different levels of representation for a term: the context, the theme and the orthography. These three approaches are studied individually and combined in order to rank translation candidates. We focus our task on French-English medical terms. Experiments on our new model show a significant improvement of the classical context-based approach, with a precision score of 80.4% for the first ranked translation candidates.

Une approche multi-vue pour l'extraction terminologique bilingue