Matching Resources in Social Environment

Abstract

User 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 hierarchical classification of tags within a cluster. The resources are reassigned 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 results of the evaluation, on the social bookmarking system del.icio.us, demonstrate significant improvements over traditional approaches.