Using trust in collaborative filtering recommendation

Abstract

Collaborative filtering (CF) technique has been widely used in recommending items of interest to users based on social relationships. The notion of trust is emerging as an important facet of relationships in social networks. In this paper, we present an improved mechanism to the standard CF techniques by incorporating trust into CF recommendation process. We derive the trust score directly from the user rating data and exploit the trust propagation in the trust web. The overall performance of our trust-based recommender system is presented and favorably compared to other approaches. © Springer-Verlag Berlin Heidelberg 2007.