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In this paper we address the problem of queries expansion and its perso nalization which consists of enriching user queries with additional information to maximiz e her satisfaction according to, e.g., her interests and her social ecosystem. While focusing on tagging systems, the proposed approach considers (i) the semantic similarity betw een ags composing a query, (ii) a social proximity between the query and the user profile for pe rsonalized expansion, and (iii) on the fly, a strategy for expanding user queries. The proposed approach has been evaluated using a large dataset crawled from del.icio.us and compared to the closest related work and the results show a clear superiority of our approach and prom ising results. MOTS-CLÉS :Personalisation, Recherche d’Information Sociale, Réseaux Sociaux.

Une Nouvelle Approche d'Expansion Sociale de Requêtes dans le Web 2.0