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SBP
2015
Springer

Modeling Group Dynamics for Personalized Group-Event Recommendation

3 years 11 months ago
Modeling Group Dynamics for Personalized Group-Event Recommendation
Event-Based Social Networks (EBSNs) such as Meetup, Plancast, etc., have become popular platforms for users to plan and organize social events with friends and acquaintances. These EBSNs provide rich online and offline user interactions, and rich event content information which can be leveraged for personalized group-event recommendations. In this paper, we propose collaborative-filtering based Bayesian models which captures group dynamics such as user interactions, usergroup membership etc., for personalized group-event recommendations. We show that modeling group dynamics learns the group preferences better than aggregating individual user preferences, and that our approach out-performs popular state-of-the-art group recommender systems. Moreover, our model provides interpretable results which can be used to study the group participations and event popularity.
Sanjay Purushotham, C.-C. Jay Kuo
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where SBP
Authors Sanjay Purushotham, C.-C. Jay Kuo
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