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KNN-Based Clustering for Improving Social Recommender Systems

  • Rong Pan
  • Peter Dolog
  • Guandong Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7607)

Abstract

Clustering is useful in tag based recommenders to reduce sparsity of data and by doing so to improve also accuracy of recommendation. Strategy for the selection of tags for clusters has an impact on the accuracy. In this paper we propose a KNN based approach for ranking tag neighbors for tag selection. We study the approach in comparison to several baselines by using two datasets in different domains. We show, that in both cases the approach outperforms the compared approaches.

Keywords

Tag Neighbors Clustering Personalization Recommender Systems Social Tagging 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rong Pan
    • 1
  • Peter Dolog
    • 1
  • Guandong Xu
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityDenmark
  2. 2.Centre for Applied InformaticsVictoria UniversityAustralia

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