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2021 , Vol. 65 >Issue 12: 101 - 111

DOI: https://doi.org/10.13266/j.issn.0252-3116.2021.12.010

RESEARCH PAPER

Explainable Personalized Recommendation Method Based on Adjustment of Users' Long- and Short-Term Preferences

  • Li Weiqing ,
  • Chi Maomao ,
  • Wang Weijun
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  • 1. School of Information Management, Central China Normal University, Wuhan 430079;
    2. Key Laboratory of Adolescent Cyber Psychology and Behavior, Ministry of Education, Wuhan 430079

Received date: 2020-12-09

  Revised date: 2021-02-24

  Online published: 2021-07-03

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Abstract

[Purpose/significance] We put forward an explainable personalized recommendation method based on adjustment of users' long- and short-preferences in view of the current problems that increasingly complexity and more feature data inputs of recommendation models, low interpretability of traditional recommendation models and over-specialization of recommendation results.[Method/process] We constructed a user preference model from two dimensions of users' recent product needs and their long-term lifestyles, used the user's rating bias and attention mechanism for reference, combined the user's long- and short-term preference with their direct score to predict the score of unknown items, and formed the Top-N recommendations.[Result/conclusion] The experimental results on two datasets showed that our method had a good performance to different user behaviors (explicit feedback or implicit feedback), different number of Top-N recommended items, and in different recommendation algorithms. It improves the accuracy, recall and diversity of the recommendation results without making great changes to various recommendation models, and based on the change of long- and short-term preference coefficients, it realizes the adjustment to the diversity and accuracy of the recommendation results, and form the corresponding recommended explanation.

Key words： personalized recommendation; user preference; explainable recommendation; adjustment of long- and short-preference

Cite this article

Li Weiqing , Chi Maomao , Wang Weijun . Explainable Personalized Recommendation Method Based on Adjustment of Users' Long- and Short-Term Preferences[J]. Library and Information Service, 2021 , 65(12) : 101 -111 . DOI: 10.13266/j.issn.0252-3116.2021.12.010

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