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A Context-Aware Collaborative Filtering Algorithm through Identifying Similar Preference Trends in Different Contextual Information

  • Phung Do
  • Hiep Le
  • Vu Thanh Nguyen
  • Tran Nam Dung
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 279)

Abstract

Three main approaches in Context-Aware Recommender Systems (CARSs) are pre-filtering, post-filtering and contextual modeling. Incorporating contextual information into main process is the different point of contextual modeling from two first approaches. In this paper, we first propose a new context-aware collaborative filtering (CACF) algorithm with contextual modeling approach combined from a clustering technique and matrix factorization method named Similar Trends Identifying (STI). We then compare the proposal with various matrix factorization-based algorithms. Overall, the STI algorithm outperforms some compared algorithms in terms of evaluation metrics and available contextual data sets.

Keywords

collaborative filtering contextual modeling clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Phung Do
    • 1
  • Hiep Le
    • 1
  • Vu Thanh Nguyen
    • 1
  • Tran Nam Dung
    • 2
  1. 1.University of Information TechnologyVietnam National University HoChiMinh CityHoChiMinh CityVietnam
  2. 2.University of Science, Vietnam National University HoChiMinh CityHoChiMinh CityVietnam

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