Publication | Closed Access
Interactive multi-party critiquing for group recommendation
53
Citations
3
References
2011
Year
Unknown Venue
Computational Social ScienceGroup RecommendersEngineeringData ScienceGroup Recommender SystemsPreference LearningSocial ComputingInteractive MarketingSocial InfluenceConventional RsConversational Recommender SystemMobile ComputingCommunicationCold-start ProblemCritiquing RsInteractive Multi-party CritiquingCollaborative Filtering
Group recommender systems (RS) are used to support groups in making common decisions when considering a set of alternatives. Current approaches generate group recommendations based on the users' individual preferences models. We believe that members of a group can reach an agreement more effectively by exchanging proposals suggested by a conventional RS. We propose to use a critiquing RS that has been shown to be effective in single-user recommendation. In the group recommendation context, critiquing allows each user to get new recommendations similar to the proposals made by the other group members and to communicate the rationale behind their own counterproposals. We describe a mobile application implementing the proposed approach and its evaluation in a live user experiment.
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