Applying Dialogue Games to Manage Recommendation in Social Networks

Recommendation in social networks is a new area of research that is still in its early beginnings. In this framework, every user can act as an individual recommender for its neighbours in the network. However, social networks are highly dynamic environments where the structure of the network and the information spread across it evolve quickly over time. In these settings, a suitable recommender must be able to manage continuous changes and to provide users with up-to-date and customised recommendations. With this aim, the theory of dialogue games has been applied to manage recommendation dialogues in social networks in this research. As a result, a dialogue game for controlling the interaction between an agent asking for recommendations to other personal agents that are its neighbours in the network has been designed. In addition, a complex decision-making policy based on this game has been developed and tested in a simulation scenario. The results are shown and discussed in this paper.