Benna, AmelMellah, HakimaChoui, IslamOualid, Ali2013-12-042013-12-042012-06-28http://dl.cerist.dz/handle/CERIST/454User comments on the web are becoming more and more important. We focus, in this paper, on the use of user-defined tags for annotating resources to identify links between them. These links are based on a social context of the resource, obtained by applying k-means classification method and a hierarchi- cal classification of tags within a cluster. The resources are re-assigned to this classification to facilitate the search process. The ranking of results is performed according to their degree of relevance, by evaluating a similarity score between the tagged contents, in hierarchical clusters of tags, and the user request. The re- sults of the evaluation, on the social bookmarking systemdel.icio.us, demonstrate significant improvements over traditional approaches.Collaborative taggingSocial information retrievalMatching resourcesConference paperSciTePress10.5220/0004088800610070