Collaborative Filtering for Predicting Users’ Potential Preferences

  • Kenta Oku
  • Ta Son Tung
  • Fumio Hattori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6884)


Our goal is to establish a method for predicting users’ potential preference. We define a potential preference as a preference for the unknown genres for the target user. However, it is difficult to predict the potential preference by conventional recommender systems because there is little or no preference data (i.e. ratings for items) for the users’ unknown genres. Accordingly, we propose a collaborative filtering for predicting the users’ potential preference by their ratings in their known genres. Experimental results using MovieLens data sets showed that the genre relevance influences the prediction accuracy of the potential preference in the unknown genres.


Collaborative filtering users’ potential preferences known and unknown genres 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Kenta Oku
    • 1
  • Ta Son Tung
    • 1
  • Fumio Hattori
    • 1
  1. 1.College of Information Science and EngineeringRitsumeikan UniversityKusatsu-cityJapan

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