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TBTF: an effective time-varying bias tensor factorization algorithm for recommender system

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Abstract

Context-aware processing is a research hotspot in the recommendation area, which achieves better recommendation accuracy by considering more context information such as time, location and etc. besides the information of the users, items and ratings. Tensor factorization is an effective algorithm in context-aware recommendation and current approaches show that adding bias to the tensor factorization model can improve the accuracy. However, users’ rating preferences fluctuate greatly over time, which makes bias fluctuate with time too. Current context-aware recommendation algorithms ignore this problem, and usually use the same bias for a user or an item in different time. Aiming at this problem, this paper first considers the time-varying effect on user bias and item bias in context-aware recommendation, and proposes a time-varying bias tensor factorization recommendation algorithm based on the bias tensor factorization model (BiasTF). We experiment on two real datasets, and the experimental results show that the proposed algorithms get better accuracy than other algorithms.

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Acknowledgements

This paper is supported by the Humanity and Social Science Fund of the Ministry of Education (No.18YJAZH136, No. 17YJCZH262), the National Key R&D Plan (No. 2018YFC0831002, No.2017YFC0804406), the National Natural Science Foundation of China (No62072288).

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Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Jianli Zhao, Shangcheng Yang & Xijiao Geng

  2. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China

    Qiuxia Sun

  3. Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia

    Huan Huo

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  1. Jianli Zhao
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  2. Shangcheng Yang
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  3. Huan Huo
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Correspondence to Jianli Zhao.

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Zhao, J., Yang, S., Huo, H. et al. TBTF: an effective time-varying bias tensor factorization algorithm for recommender system. Appl Intell 51, 4933–4944 (2021). https://doi.org/10.1007/s10489-020-02035-1

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