Deep mining method of online learning behaviour data based on big data analysis Online publication date: Wed, 19-Jul-2023
by Weijuan Li
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 33, No. 4/5, 2023
Abstract: Aiming at the problems of low mining accuracy and long mining time in learning behaviour data mining, a deep mining method of online learning behaviour data based on big data analysis is proposed. The initial signals of learners' subject, object, learning environment, learning means, time and result data are set, and the data components of online learning behaviour are obtained through EMD. EEMD is used to extract the key features of online learning behaviour data, and different contribution rates in learning sequence are calculated by linear weighting method. With the help of the first-order polynomial decision function in big data technology, the inner product is calculated, and the online learning behaviour data deep mining model based on big data technology is constructed to complete the data deep mining. The experimental results show that the accuracy of the proposed method is about 95%, and the mining time is short.
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 Continuing Engineering Education and Life-Long Learning (IJCEELL):
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