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In this article we describe the use of Natural Language Processing platform to interpred user queries to be fed into a question-answering system. The advantage of this system is threefold: first, we are able to identify only those requests which correspond to factual questions for which the engine has a precise answer; second, error correction is semantically controlled, in order to avoid bad or missing answers due to typos and third the language processing is used to disambiguate ambiguous word forms. With this interpretation we are able to identify and respond to four times as many queries as without interpretation with an accuracy rate > 98%. MOTS-CLÉS : moteur de recherche, moteur de questions réponses, traitement automatique des langues naturelles, web sémantique

Interprétation linguistique de requêtes pour un moteur de questions réponses grand public