A Hybrid Recommendation List Aggregation Algorithm for Group Recommendation
Yuankun Ma, Shujuan Ji, Yongquan Liang, Jianli Zhao, Yongfeng Cui · 2015
In group-oriented recommendation filed, the design of a commonly acceptable recommendation list is a tough task. Traditional group recommendation algorithms often realize group recommendation list aggregation according to item ranking or item score of group members' recommendation lists. The factors considered in these algorithms are relatively one-sided. This paper puts forward a new HAaB aggregation algorithm for list aggregation, which considers the item ranking as well as the item score of the members' recommendation lists. Experimental results show that HAaB algorithm can obviously outperform the traditional group recommendation algorithms when recommending for various common combinations of groups.