Group Recommendation for Smart Applications: A Multi-agent View of the Problem

The widespread use of social networks is modifying our way to live our cities and to plan/decide our activities. The long-term goal of our research is to provide users with group recommendation and decision support systems for smart city applications that rely on the analysis of the users’ behaviors on social networks/media. In this paper, we provide an overview of the group recommendation literature from a game-theoretical/multiagent system classical point of view, and we present a practical example where a social choice mechanism is extended with social information extracted from the analysis of the interactions, within small groups of users, on a social network.