Tag-Based collaborative filtering recommendation algorithm for TV program
Fulian Yin, Xiaowei Liu, Wanying Ding, Ruizhe Zhang · 2016
In this paper, we present a tag-based recommendation system which generates personalized recommendations for TV users. The proposed approach, based on collaborative filtering recommendation algorithm, uses similarity calculation and vector production to process the users' data. In order to test the applicability of this method, we operated several experiments on random users' data, and the overall result reached the accuracy rate of 9.5%, the recall rate of 12.9%, and the coverage rate of 11.7%, the average popularity level of 1.92.