Social group recommendation using topic models

Jing Wang and Hui Zhao

Abstract

In this paper, we take the user influence and their relationship into account to propose a new group recommendation method, which utilizes the topic oriented analysis to calculate the user influence on specific topic and to construct topical sub-groups. Based on these topical sub-groups, different user factors are used to depict the topical sub-group characteristics more properly and to calculate the user influence (including individual and social) on the topical sub-groups. Experimental results demonstrate the effectiveness and efficiency of the proposed method, and also show that the proposed method can improve the prediction accuracy of the group recommendation.