Matching Resources in Social Environment

dc.citation.epage70fr_FR
dc.citation.spage61fr_FR
dc.contributor.authorBenna, Amel
dc.contributor.authorMellah, Hakima
dc.contributor.authorChoui, Islam
dc.contributor.authorOualid, Ali
dc.date.accessioned2013-12-04T11:33:07Z
dc.date.available2013-12-04T11:33:07Z
dc.date.issued2012-06-28
dc.description.abstractUser 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.fr_FR
dc.identifier.doi10.5220/0004088800610070
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/454
dc.relation.ispartofInternational Workshop on Web Intelligence in conjunction with International Conference on Entreprise Information systems (ICEIS)fr_FR
dc.relation.placeWroclaw, Polandfr_FR
dc.rights.holderSciTePressfr_FR
dc.structureIntégration des Systèmes d'Informationfr_FR
dc.subjectCollaborative taggingfr_FR
dc.subjectSocial information retrievalfr_FR
dc.subjectMatching resourcesfr_FR
dc.titleMatching Resources in Social Environmentfr_FR
dc.typeConference paper
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