Matching Resources in Social Environment

dc.contributor.authorBenna, Amel
dc.description.abstractUser comments on web become 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 resource social context, obtained by applying k-means classification method and a hierarchical classification of tags within a cluster. The resources are re-assigned to this classification, to facilitate search process, and the ranking of result 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 results of the evaluation, on social bookmarking system, demonstrate significant improvements over traditional approaches.fr_FR
dc.relation.ispartofRapports de recherche internes
dc.structureSystèmes et Documents Multimédia Structurés (SDMS)fr_FR
dc.subjectLinkage informationfr_FR
dc.subjectCollaborative taggingfr_FR
dc.subjectSocial information retrievalfr_FR
dc.titleMatching Resources in Social Environmentfr_FR
dc.typeTechnical Report