A Video Resource Recommendation System Based on Deep Learning
Yunxuan Zhao · Advances in transdisciplinary engineering · 2024
To recommend video resources in education for better results, this article attempts to use a deep learning model to construct a system suitable for mobile devices. According to the specific design principles and requirements analysis, the overall logical framework of the system and the main technology of development are provided. Then the composition of server and client is explained by B/S system architecture, and the function realization scheme of key modules of the system is provided by video coding and compression technology, MSSQL database technology and ASP.NET. The recommendation module adopts the deep learning lightweight model MobileNet to improve detection speed and accuracy, and reduce memory, which achieves real-time detection and pushing effects. The empirical analysis of the system shows that it has the characteristics of simple and fast interface, safe and reliable. It also realizes the mining and matching of massive potential information in videos, so it has an important auxiliary role for the ideological and political teaching.