Title: MOOC English online course recommendation algorithm based on LDA user interest model

Authors: Zhongping Yao

Addresses: School of Foreign Languages, Jiujiang University, Jiujiang 332005, Jiangxi, China

Abstract: In order to improve the efficiency and accuracy of course recommendation and improve user satisfaction, a MOOC English online course recommendation algorithm based on LDA user interest model is proposed. Wavelet transform method is used for data denoising to improve the accuracy of recommendation results. Using support vector machine to classify courses to improve the efficiency of course recommendation, LDA user interest model is established to describe the characteristics of students' online learning behaviour. According to the characteristics of students' interest and learning behaviour, the matching topics can be selected to realise English online course recommendation. The experimental results show that the highest accuracy of course recommendation of this method is 92%, and the student satisfaction basically reaches more than 90 points, which verifies the effectiveness of this method.

Keywords: LDA user interest model; course recommendation; wavelet transform; support vector machine; SVM; data denoising.

DOI: 10.1504/IJCEELL.2024.136991

International Journal of Continuing Engineering Education and Life-Long Learning, 2024 Vol.34 No.2/3, pp.143 - 154

Received: 14 Mar 2022
Accepted: 12 Jul 2022
Published online: 01 Mar 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article