A Comparison of Content-Based Tag Recommendations in Folksonomy Systems

  • Jens Illig
  • Andreas Hotho
  • Robert Jäschke
  • Gerd Stumme
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6581)

Abstract

Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jens Illig
    • 1
  • Andreas Hotho
    • 1
  • Robert Jäschke
    • 1
    • 2
  • Gerd Stumme
    • 1
    • 2
  1. 1.Knowledge & Data Engineering Group, Department of Mathematics and Computer ScienceUniversity of KasselKasselGermany
  2. 2.Research Center L3SHannoverGermany

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