Mining the social semantic Web for making cross-domain recommendations

This is an electronic version of the paper presented at the Fifth BCS-IRSG Symposium on Future Directions in Information Access, held in Granada on 2003Cross-domain recommender systems filter and suggest items in a target domain by exploiting user preferences and/or domain knowledge available in a (likely related) source domain. In our research we are developing a framework for cross-domain recommendation capable of mining heterogeneous sources of information available in the so-called Social Semantic Web, such as semantically annotated data, user generated contents, and contextual signals