Title: University online teaching resource sharing open platform based on deep learning

Authors: Liangxi Ding

Addresses: Intelligent Education Industry Research Institute, Nanchang Institute of Technology, Nanchang, 330044, China

Abstract: Aiming at the problems of high energy consumption, low classification accuracy of shared data and poor sharing effect of open network teaching resource sharing platform, an open network teaching resource sharing platform based on deep learning is designed. First, the application module, database module, and database retrieval function module are setup on the platform. Then, online teaching resources are classified in colleges and universities by using deep learning algorithms, and the characteristics of online teaching resources in colleges and universities are determined. Finally, an open platform for sharing online teaching resources in colleges and universities is built. The experimental results show that the platform designed in this paper has low energy consumption, which is always lower than 20 j, and the data classification accuracy of shared online teaching resources is always higher than 90%, which can effectively improve the sharing effect of online teaching resources in colleges and universities, and has good practical application performance.

Keywords: deep learning; application module; database module; database retrieval function module; softmax regression.

DOI: 10.1504/IJCEELL.2024.139930

International Journal of Continuing Engineering Education and Life-Long Learning, 2024 Vol.34 No.4, pp.299 - 313

Received: 20 Apr 2022
Accepted: 30 Aug 2022
Published online: 12 Jul 2024 *

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