Matching Resources in Social Environment

Abstract

User 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.