Research on book recommendation algorithm based on attribute comprehensive similarity
Xiuting Chi, Quanzhou Huang · 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) · 2022
The common problems of less user information and missing item ratings in recommended systems greatly affect the accuracy of recommending users. Aiming at this problem, a collaborative filtering algorithm based on comprehensive similarity of attributes is proposed. Its application in book recommendation improves the utilization of resources and the quality of recommendation service, and improves the accuracy of book recommendation.