A Fuzzy Set Based Approach for Rating Bias

  • Mingming Li University of Chinese Academy of Sciences
  • Jiao Dai University of Chinese Academy of Sciences
  • Fuqing Zhu University of Chinese Academy of Sciences
  • Liangjun Zang University of Chinese Academy of Sciences
  • Songlin Hu University of Chinese Academy of Sciences
  • Jizhong Han University of Chinese Academy of Sciences

Abstract

In recommender systems, the user uncertain preference results in unexpected ratings. This paper makes an initial attempt in integrating the influence of user uncertain degree into the matrix factorization framework. Specifically, a fuzzy set of like for each user is defined, and the membership function is utilized to measure the degree of an item belonging to the fuzzy set. Furthermore, to enhance the computational effect on sparse matrix, the uncertain preference is formulated as a side-information for fusion. Experimental results on three real-world datasets show that the proposed approach produces stable improvements compared with others.

Published
2019-07-17
Section
Student Abstract Track