An adaptive correlation-based group recommendation system
Kuei-Hong Lin, Yu-Shian Chiu, Jia-Sin Chen · 2011
An adaptive correlation-based group recommendation system or recommender is proposed which takes the members' interactions into account. Thus, the proposed method can predict members' relationships by acquiring the correlations between a group and its members. With the predicted correlations, each member's weight can be estimated. Finally, the group's ratings of those non-rated items can be predicted by merging members' ratings and their estimated weights. Without complex computation, the proposed group recommendation system can achieve accurate predictions of the group's ratings. Therefore, it suits for helping a group to make decisions since its members have different opinions for selecting multimedia contents.