A knowledge set recommendation method for online education in universities based on DV-TransE model and social networks Online publication date: Wed, 21-Feb-2024
by Die Meng; Beibei Ma; Zhanlei Shang
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 30, No. 1, 2024
Abstract: In order to improve the recommendation accuracy of existing online education knowledge sets in universities and shorten the recommendation response time, a recommendation method for online education knowledge sets in universities based on DV-TransE model and social network is proposed. This method is first based on the principle of knowledge graph, extracting descriptive features of the knowledge set, and introducing the TransE algorithm to construct the DV-TransE model of the online education knowledge set in universities. Then, based on social networks, the similarity between users is calculated, and finally, it is combined with the constructed knowledge set DV-TransE model to achieve recommendation of online education knowledge sets in universities. The experimental results show that after the application of the proposed method, its recommended response time is less than 14.5 ms, and the recommendation accuracy is as high as 95%, which is superior to the comparison method.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and 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
Our Blog 
Follow us on Twitter 
Visit us on Facebook