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Web 2.0 technologies put the user at the center of data production and introduce a strong social collaboration. Therefore, the techniques used in traditional information retrieval systems do not meet the requirements of users who want to take into account their social preferences. The idea reported in this paper is about including not only the social context of the user but also the one for the resource. In the social network that we consider, the user social context brings its interests, which are captured from a collaborative tagging system, while the resource social context is related to clusters of tags, obtained by classification method, and users' opinions according to their expertise level on the resource. The results of our experiment evaluation on real-world datasets (crawled from delicious folksonomy) demonstrate significant improvements over traditional retrieval approaches.