Combining users and items rankings for group decision support

Abstract

Traveling and city sightseeing are, in most cases, activities that involve small groups of users. Hence, a content personalization process, in a travel domain, requires taking into account simultaneously the preferences of different users. Moreover, a group recommendation system should also capture the possible intra-group relationships, which are fundamental features in a group decision process. In this paper, we model this problem as a multi-agent aggregation of preferences by using weighted social choice functions. In this context, weights can be extracted by analyzing the interactions of the group’s members on Online Social Networks.