Journal of Information Processing Systems

  • 제17권3호
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  • Pages.462-472
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  • 2021
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Effective Pre-rating Method Based on Users' Dichotomous Preferences and Average Ratings Fusion for Recommender Systems

  • Cheng, Shulin (The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University) ;
  • Wang, Wanyan (School of Computer and Information, Anqing Normal University) ;
  • Yang, Shan (School of Computer and Information, Anqing Normal University) ;
  • Cheng, Xiufang (School of Computer and Information, Anqing Normal University)
  • 투고 : 2020.12.30
  • 심사 : 2021.03.26
  • 발행 : 2021.06.30
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초록

With an increase in the scale of recommender systems, users' rating data tend to be extremely sparse. Some methods have been utilized to alleviate this problem; nevertheless, it has not been satisfactorily solved yet. Therefore, we propose an effective pre-rating method based on users' dichotomous preferences and average ratings fusion. First, based on a user-item ratings matrix, a new user-item preference matrix was constructed to analyze and model user preferences. The items were then divided into two categories based on a parameterized dynamic threshold. The missing ratings for items that the user was not interested in were directly filled with the lowest user rating; otherwise, fusion ratings were utilized to fill the missing ratings. Further, an optimized parameter λ was introduced to adjust their weights. Finally, we verified our method on a standard dataset. The experimental results show that our method can effectively reduce the prediction error and improve the recommendation quality. As for its application, our method is effective, but not complicated.

키워드

과제정보

The work was supported by grants from the Nature Science Foundation of Anhui Province in China (No. 2008085MF193 and 1908085MF194), the Natural Science Research Foundation of the Education, Department of Anhui Province of China (No. KJ2019A0578); the Outstanding Young Talents Program of Anhui Province (No. gxyqZD2018060).

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