The Method of Personalized Recommendation with Ensemble Combination

Nowadays trust and reputation models are becoming more and more important to make the decision through various industries. Trust-based system is vulnerable to sparse relations, so there are attempts to combine the trust and reputation models. In this paper, we propose a method in which the trust and reputation models are harmonized through an ensemble combination. It can be applied to not only the personalized recommendations but also the detection of malicious insider users which attack with unfair rating. The proposed method enables both the models to complement each other and provides the reliably personalized service.