gRecs: a group recommendation system based on user clustering

Authors:
Irene Ntoutsi;Kostas Stefanidis;Kjetil Norvag;Hans-Peter Kriegel
Affiliations:
Institute for Informatics, Ludwig Maximilian University, Munich, Germany;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Institute for Informatics, Ludwig Maximilian University, Munich, Germany
Venue:
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Year:
2012

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Abstract

In this demonstration paper, we present gRecs, a system for group recommendations that follows a collaborative strategy. We enhance recommendations with the notion of support to model the confidence of the recommendations. Moreover, we propose partitioning users into clusters of similar ones. This way, recommendations for users are produced with respect to the preferences of their cluster members without extensively searching for similar users in the whole user base. Finally, we leverage the power of a top-k algorithm for locating the top-k group recommendations.