Crowd-voting-based group recommender systems

Abstract

In this paper, we deal with group recommendations where the task is to choose a sequence of natural attractions that better matches the expectation of a group of tourists. We show in this setting, that the crowd support in selecting potential alternatives, may help members to preserve the harmony of their group and not deviating too much from each other as well. Taking into consideration each member preferences, we tackle the consensus joint decision as a voting process that builds a majority opinion about a sequence of the most interesting natural attractions to visit by the group. Beyond consensus joint decision, it's possible afterwards to perform better group satisfaction by improving the collective gain based on a likewise genetic mutation operation. Preliminary experimental results show that the proposed approach may outperform better when there is a higher heterogeneity between group members voting.