User modeling in the social web

Abstract

This paper presents the idea to reason over user's tags to define and enrich the user model. We apply our approach to an adaptive web-based and multi-device social recommender system: iCITY, which exploits a tag-based user model, enriched from the information derived from the tags inserted in the system by users, and filled also with the tags the user has already exploited in other social web sites. Moreover, we propose an architecture to enable the iCITY tag-based user model be exported and shared with other social applications in a semantic enhanced way. Finally, we propose the sharing of the user profile, together with the list of tags, in a shared syntax (such as RDF(S), OWL, RSS). © Springer-Verlag Berlin Heidelberg 2007.