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    Mining the Social Semantic Web for making cross-domain recommendations

    Fifth BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2013)

    3 September 2013, Granada, Spain


    Ignacio Fernández-Tobías


    Cross-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.


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