A Hybrid Recommendation List Aggregation Algorithm for Group Recommendation

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.