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Preference Structure and Similarity Measure in Tag-Based Recommender Systems

  • Xi Yuan
  • Jia-jin Huang
  • Ning Zhong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

Social tagging systems extend recommender systems from the pair (user, item) to (user, item, tag). This paper discusses the framework of similarity measure on (user, item, tag) from qualitative and quantitative perspectives. The qualitative measure makes use of the preference structure relation on (user, item, tag), and the quantitative measure makes use of reflection on (user, item, tag). The k nearest neighbors and reverse k′ nearest neighbors are used to generate recommendations.

Keywords

Recommender System Target User Collaborative Filter Mean Absolute Error Rating Preference 
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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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Xi Yuan
    • 1
    • 2
  • Jia-jin Huang
    • 1
    • 2
  • Ning Zhong
    • 1
    • 2
  1. 1.International WIC InstituteBeijing University of TechnologyChina
  2. 2.Department of Life Science and InformaticsMaebashi Institute of TechnologyMaebashiJapan

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