Title: MOOC English online learning resource recommendation algorithm based on spectral clustering and matrix decomposition

Authors: Qichao Huang

Addresses: Department of Foreign Languages, Shangqiu Normal University, Shangqiu, 476000, China

Abstract: In order to overcome the problems of low recommendation accuracy and long recommendation time in traditional MOOC English online learning resource recommendation algorithm, a new MOOC English online learning resource recommendation algorithm based on spectral clustering and matrix decomposition is proposed. The clustering objective function is constructed by spectral clustering method to complete the clustering of MOOC English online learning resources. Based on the results of resource clustering, the objective matrix, row auxiliary matrix and column auxiliary matrix are constructed. The matrix decomposition method is used to construct the recommended scoring matrix, and the scoring matrix is filled and reduced to complete the recommendation of MOOC English online learning resources. Experimental results show that, compared with the traditional learning resource recommendation, the proposed algorithm has higher clustering accuracy, higher recommendation accuracy and efficiency, and the maximum recommendation time is only 1.1 s.

Keywords: spectral clustering; matrix decomposition; MOOC English online learning; learning resources recommendation.

DOI: 10.1504/IJCEELL.2023.132411

International Journal of Continuing Engineering Education and Life-Long Learning, 2023 Vol.33 No.4/5, pp.376 - 387

Received: 06 May 2021
Accepted: 09 Aug 2021
Published online: 19 Jul 2023 *

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