Title: Study on recommendation method of high quality MOOC English teaching resources based on fuzzy clustering

Authors: Zhongping Yao; Xiao Zheng

Addresses: School of Foreign Languages, Jiujiang University, Jiujiang 332005, Jiangxi, China ' Jiujiang University Affiliated Hospital, Jiujiang 332001, Jiangxi, China

Abstract: In order to improve the mining and recommendation accuracy of high-quality teaching resources, a new recommendation method of high quality teaching resources is developed according to fuzzy clustering algorithm. Firstly, fuzzy clustering method is used to mine high quality MOOC English teaching resources to improve the effectiveness and accuracy of mining. Secondly, it analyses the main factors affecting learners' learning preferences and constructs a teaching resource recommendation model. Finally, the linear weighting method is used to construct the recommended objective function, and the constraints of the function are set. The recommendation can be realised by solving the function under relevant constraints. The experimental results show that compared with the traditional recommendation methods, the resource mining accuracy of this method is higher, and the recommendation accuracy is higher, which is always maintained at more than 97%.

Keywords: fuzzy clustering; high quality MOOC resources; English teaching; resource recommendation.

DOI: 10.1504/IJRIS.2022.126653

International Journal of Reasoning-based Intelligent Systems, 2022 Vol.14 No.4, pp.208 - 214

Received: 12 Apr 2022
Accepted: 30 May 2022

Published online: 31 Oct 2022 *

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