Design and Implementation of Short Video Recommendation Algorithm Based on Latent Factor Model
Xinyu Huang, Deqiang Shi, Linge Wang · 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) · 2021
With the continuous Internet development, network information amount has increased significantly. In this way, users faced with extensive network information cannot quickly find information that meets their needs, leading to decreased efficiency in network information usage. Accordingly, personalized recommendation system should be an important part of the electronic platform system as recommendation efficiency directly affects the user experience and the use of electronic platforms. In recent years, the data of electronic platforms presents a trend of massive growth, resulting in decreased accuracy in system recommendations, increased errors, and decreased efficiency. Therefore, it is particularly necessary to study and analyze personalized recommendation algorithms. Based on the research and application of latent factor model in short video recommendation algorithm, this paper aims to recommend users with video content that truly meets user needs and interests.