Optimizing preferences within groups: a case study on travel recommendation..

Abstract

This work describes a multiagent recommender system where agents work on behalf of members of a group of customers, trying to reach the best recommendation for the whole group. The goal is to model the group recommendation as a distributed constraint optimization problem, taking customer preferences into account and searching for the best so- lution. Experimental results show that this approach can be sucessfully applied to propose recommendations to a group of users.