Wavelet-based collaborative filtering for adapting changes in user behavior

Cheon Hyeonjae, Lee Hongchul, Um Insup

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recommendation systems help users find the information, products and services they most want to find. Collaborative filtering is the method of making automatic predictions about the interest of a user by collecting interest information from many users, which has been very successful recommendation technique for recommendation systems in both research and practice. However, the traditional collaborative filtering is slow to detect the interest of a user changing with time as a case of user behavior and to adapt the changes, because the traditional collaborative filtering uses Pearson's correlation coefficient between users with the numerous values of property. In this paper, we apply the wavelet analysis to collaborative filtering in order to reveal the trends hidden in the interest of a user and propose the wavelet-based collaborative filtering for adapting changes in user behavior. The results of the performance evaluation show that the proposed wavelet-based collaborative filtering makes the improvement in the personalized recommendations.

Original languageEnglish
Title of host publicationDigital Libraries
Subtitle of host publicationAchievements, Challenges and Opportunities - 9th International Conference on Asian Digital Libraries, ICADL 2006, Proceedings
PublisherSpringer Verlag
Pages470-473
Number of pages4
ISBN (Print)3540493751, 9783540493754
Publication statusPublished - 2006
Event9th International Conference on Asian Digital Libraries, ICADL 2006 - Kyoto, Japan
Duration: 2006 Nov 272006 Nov 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4312 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Asian Digital Libraries, ICADL 2006
CountryJapan
CityKyoto
Period06/11/2706/11/30

Keywords

  • Collaborative filtering
  • Recommendation system
  • User behavior
  • Wavelet analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Hyeonjae, C., Hongchul, L., & Insup, U. (2006). Wavelet-based collaborative filtering for adapting changes in user behavior. In Digital Libraries: Achievements, Challenges and Opportunities - 9th International Conference on Asian Digital Libraries, ICADL 2006, Proceedings (pp. 470-473). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4312 LNCS). Springer Verlag.