Research on Latent Semantic Model and user model-based video recommendation Algorithm

摘要

The rapid progress of Internet technology brings new opportunities for the development of science and technology, and the emerging network video technology is gradually penetrated into people's daily life. Due to the rapid development, the plentiful video contents also make everyone dazzling, at the same time, the video users with multiple geometric growth also make the network video operators not know what to do, and the fundamental technology to solve this problem is video recommendation technology. This paper presents an algorithm combined with the neighborhood latent semantic model, the new model retains the characteristics of recommended explanation in neighborhood algorithm, and expands based on implicit feedback information of users, which has further improved the recommendation efficiency. The new model adopts the field method of User-CF, this paper will compare the operational effects of basis latent semantic and the latent semantic fusing User-CF neighborhood mode to achieve the purpose of simulation.