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Analysis and Evaluation of Recommendation Systems

  • Emiko Orimo
  • Hideki Koike
  • Toshiyuki Masui
  • Akikazu Takeuchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4557)

Abstract

Popular online services, such as Amazon.com, provide recommendations for users by using other users’ rating scores for items. In this study, we describe three types of rating systems: score-rated, count-rated, and digital-rated. We hypothesize that digital-rated systems provide the most useful recommendations. Then we analyze the differences in the results of the rating when the granularity of the score changes. Finally, we visualize users by developing a 2-D visualization system that uses a multi-dimensional scaling method.

Keywords

recommendation system rating algorithm multi-dimensional scaling method visualization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Emiko Orimo
    • 1
    • 2
  • Hideki Koike
    • 2
  • Toshiyuki Masui
    • 3
  • Akikazu Takeuchi
    • 1
  1. 1.So-net Entertainment Corporation 
  2. 2.University of Electro-Communications 
  3. 3.Apple Computer Inc. 

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