University online teaching resource sharing open platform based on deep learning
by Liangxi Ding
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 34, No. 4, 2024

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.

Online publication date: Fri, 12-Jul-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com