Time-Sensitive Collaborative Filtering Algorithm with Feature Stability

Year, pages: 2020, 141 - 155

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.

Pang, S., Yu, S., Li, G., Qiao, S., Wang, M. 2020. Time-Sensitive Collaborative Filtering Algorithm with Feature Stability. In Computing and Informatics, vol. 39, no.1-2, pp. 141-155. 1335-9150. DOI: https://doi.org/10.31577/cai_2020_1-2_141

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. 1335-9150. DOI: https://doi.org/10.31577/cai_2020_1-2_141

Publisher: Ústav informatiky SAV