Matching Resources in Social Environment

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dc.contributor.authorBenna, Amel
dc.date.accessioned2013-11-25T15:14:20Z
dc.date.available2013-11-25T15:14:20Z
dc.date.issued2012-05
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 del.icio.us, demonstrate significant improvements over traditional approaches.fr_FR
dc.identifier.isrnCERIST-DSISM/RR--12-000000013--dzfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/373
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.placeAlger
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
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