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

DOI

10.2991/mcei-17.2017.96How to use a DOI?

Keywords

Video recommendation; Latent semantic model; Neighborhood method; Fusion.

Abstract

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Fuhao Yang
AU  - Shaofu Lin
PY  - 2017/12
DA  - 2017/12
TI  - Research on Latent Semantic Model and user model-based video recommendation Algorithm
BT  - Proceedings of the 2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017)
PB  - Atlantis Press
SP  - 445
EP  - 451
SN  - 2352-538X
UR  - https://doi.org/10.2991/mcei-17.2017.96
DO  - 10.2991/mcei-17.2017.96
ID  - Yang2017/12
ER  -