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Title: A study on the dynamic mining of English teaching resources using dynamic minimum support

Authors: Jin Zhang; Jinghui Liu; Bing Hu

Addresses: School of Foreign Languages, Handan University, Handan, Hebei, China ' School of Foreign Languages, Handan University, Handan, Hebei, China ' School of Foreign Languages, Handan University, Handan, Hebei, China

Abstract: In order to improve the accuracy of dynamic mining of English teaching resources and shorten response time, a dynamic mining method for English teaching resources based on dynamic minimum support is proposed. Firstly, convert unstructured data into structured features to achieve feature extraction of English teaching resources. Secondly, the mutual information matrix and diagonalisation method are used to calculate the eigenvalues and eigenvectors, and the principal component decision matrix is constructed to achieve dimensionality reduction. Finally, based on dynamic minimum support mining technology, the threshold is adjusted in real-time to meet teaching needs. The prefix span algorithm is used to process incremental data, and when changing support, the updated itemset is scanned and filtered. The effective sequence is integrated with confidence level. The experimental results show that the mining accuracy of our method is stable at over 95%, and the response time remains between 0.62 s and 0.92s.

Keywords: dynamic minimum support; English teaching resources; dynamic mining; mutual information matrix.

DOI: 10.1504/IJCAT.2026.153740

International Journal of Computer Applications in Technology, 2026 Vol.78 No.6, pp.89 - 97

Received: 28 Sep 2025
Accepted: 09 Dec 2025
Published online: 22 May 2026 *