Time-Sensitive Collaborative Filtering Algorithm with Feature Stability

Authors

  • Shanchen Pang Shandong University of Science and Technology, Qingdao, China
  • Shihang Yu Shandong University of Science and Technology, Qingdao, China
  • Guiling Li Shandong University of Science and Technology, Qingdao, China
  • Sibo Qiao Shandong University of Science and Technology, Qingdao, China
  • Min Wang Shandong University of Science and Technology, Qingdao, China

DOI:

https://doi.org/10.31577/cai_2020_1-2_141

Keywords:

Collaborative filtering, recommendation algorithm, long tail, time-sensitive

Abstract

In the recommendation system, the collaborative filtering algorithm is widely used. However, there are lots of problems which need to be solved in recommendation field, such as low precision, the long tail of items. In this paper, we design an algorithm called FSTS for solving the low precision and the long tail. We adopt stability variables and time-sensitive factors to solve the problem of user's interest drift, and improve the accuracy of prediction. Experiments show that, compared with Item-CF, the precision, the recall, the coverage and the popularity have been significantly improved by FSTS algorithm. At the same time, it can mine long tail items and alleviate the phenomenon of the long tail.

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Published

2020-02-29

How to Cite

Pang, S., Yu, S., Li, G., Qiao, S., & Wang, M. (2020). Time-Sensitive Collaborative Filtering Algorithm with Feature Stability. Computing and Informatics, 39(1-2), 141–155. https://doi.org/10.31577/cai_2020_1-2_141

Issue

Section

Special Section Articles