Recommendation incorporating transition of temporally intensive unity

Kenta Inuzuka, Tomonori Hayashi, Tomohiro Takagi

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

Abstract

It is important to note that user preferences change over time. However, it is not guaranteed that user preferences change at a steady rate. For example, a person who intensively listens to music of the same artist might intensively listen to the music of a different artist after a few days. For this reason, it is effective to incorporate such preference changes into recommender systems. In this paper, we propose an approach that predicts user preferences with consideration of preference changes by learning the transition of the preference that is the temporally intensive unity of purchasing items as one preference. Our approach is composed of a Kalman filter and matrix factorization. We show through experiments using a real-world dataset that our approach outperforms competitive methods such as the first order Markov model.

Original languageEnglish
Title of host publication2016 IEEE 9th International Workshop on Computational Intelligence and Applications, IWCIA 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages21-26
Number of pages6
ISBN (Electronic)9781509027750
DOIs
Publication statusPublished - 4 Jan 2017
Event9th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2016 - Hiroshima, Japan
Duration: 5 Nov 2016 → …

Publication series

Name2016 IEEE 9th International Workshop on Computational Intelligence and Applications, IWCIA 2016 - Proceedings

Conference

Conference9th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2016
CountryJapan
CityHiroshima
Period5/11/16 → …

Keywords

  • Kalman Filter
  • Matrix Factorization
  • Time-Aware Recommendation

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  • Cite this

    Inuzuka, K., Hayashi, T., & Takagi, T. (2017). Recommendation incorporating transition of temporally intensive unity. In 2016 IEEE 9th International Workshop on Computational Intelligence and Applications, IWCIA 2016 - Proceedings (pp. 21-26). [7805743] (2016 IEEE 9th International Workshop on Computational Intelligence and Applications, IWCIA 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWCIA.2016.7805743