Najeh Naffakhi

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In this paper, we are interested in aggregated search in structured document in XML. For this, we present a model for the structured information retrieval, based on the Bayesian networks theory. Relations query-terms and terms-elements are modelled through probability measures. In this model, the user's query starts a process of propagation to recover the(More)
In this paper, we are interested in aggregated search in structured XML documents. We present a structured information retrieval model based on the Bayesian networks theory. Query-terms and terms-elements relations are modeled through probability. In this model, the user's query starts a propagation process to recover the XML elements. Thus, instead of(More)
In this paper, we are interested in aggregated search in structured XML documents. We present a structured information retrieval model based on the Bayesian networks theory. Relations query-terms and terms-elements are modeled through probability. In this model, the user's query starts a process of propagation to recover the elements. Thus, instead of(More)
Un problème important de la production automatique de règles de classification concerne la durée de génération de ces règles ; en effet, les algorithmes mis en oeuvre produisent souvent des règles pendant un certain temps assez long. Nous proposons une nouvelle méthode de classification à partir d'une base de données images. Cette méthode se situe à la(More)
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