A negotiation framework for heterogeneous group recommendation

Over the last years, some remarkable recommender systems for group of users have been developed. When using most of these systems, each group member communicates his/her preferences to the system, which obtains a group profile as the result of an equal weighting of the individual preferences. This way, no member is particularly dissatisfied with the recommendations. However, this is not a realistic situation, given that not all the members in a group act in the same manner. This paper deals with the problem of recommendation for a group of users, where, besides his/her own preferences, each user may have different expectations about the result of the recommendation and may exhibit a different behaviour with respect to the other group members. Moreover, all this information is private and may be revealed under certain circumstances. In this context, we have opted for building a multi-agent system, where an agent acts on behalf of one group member. We have implemented a UserAgent that can be configured in order to exhibit the behaviour desired by the corresponding user. Then, different UserAgents negotiate with the aim of building a group profile that satisfies their particular minimum requirements, while preserving some privacy. Moreover, we have designed a NegotiatorAgent, which governs the negotiation and may act as a mediator in order to facilitate the agreement. Finally, we have performed some experiments that show that this mechanism is able to give a response in this heterogeneous environment.