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gRecs: A Group Recommendation System Based on User Clustering

  • Irene Ntoutsi
  • Kostas Stefanidis
  • Kjetil Norvag
  • Hans-Peter Kriegel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7239)

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.

Keywords

Relevance Score Similar User Personal Recommendation Group Recommendation User Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Irene Ntoutsi
    • 1
  • Kostas Stefanidis
    • 2
  • Kjetil Norvag
    • 2
  • Hans-Peter Kriegel
    • 1
  1. 1.Institute for InformaticsLudwig Maximilian UniversityMunichGermany
  2. 2.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway

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