Title: An English MOOC similar resource clustering method based on grey correlation

Authors: Xianzhuang Mao

Addresses: Foreign Languages Department, Henan University of Economics and Law, Zhengzhou, 450046, China

Abstract: Due to the problems of low clustering accuracy and efficiency in traditional similar resource clustering methods, this paper studies an English MOOC similar resource clustering method based on grey correlation. Principal component analysis was used to extract similar resource features of English MOOC, and feature selection methods was used to pre-process similar resource features of English MOOC. On this basis, based on the grey correlation method, the pre-processed English MOOC similar resource features are standardised, and the correlation degree between different English MOOC similar resource features is calculated. The English MOOC similar resource correlation matrix is constructed to achieve English MOOC similar resource clustering. The experimental results show that the contour coefficient of the proposed method is closer to one, and the clustering accuracy of similar resources in English MOOC is as high as 94.2%, with a clustering time of only 22.3 ms.

Keywords: grey correlation; principal component analysis method; English MOOC; feature selection; clustering of similar resources.

DOI: 10.1504/IJBIDM.2024.140878

International Journal of Business Intelligence and Data Mining, 2024 Vol.25 No.3/4, pp.350 - 361

Received: 16 Aug 2023
Accepted: 16 Nov 2023
Published online: 03 Sep 2024 *

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