A generic semantic-based framework for cross-domain recommendation

Abstract

In this paper, we present an ongoing research work on the design and development of a generic knowledge-based description framework built upon semantic networks. It aims at integrating and exploiting knowledge on several domains to provide cross-domain item recommendations. More specifically, we propose an approach that automatically extracts information about two different domains, such as architecture and music, which are available in Linked Data repositories. This enables to link concepts in the two domains by means of a weighted directed acyclic graph, and to perform weight spreading on such graph to identify items in the target domain (music artists) that are related to items of the source domain (places of interest).