Title: Online allocation of network learning resources based on parallel cluster mining

Authors: Zhaofeng Li; Ping Hu; Pei Zhang; Liwei Zhang

Addresses: School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan Province, 453003, China ' School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan Province, 453003, China ' School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan Province, 453003, China ' School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan Province, 453003, China

Abstract: In order to solve the problem of low accuracy and consideration of online allocation of existing network learning resources, this paper proposes a network learning resource online allocation method based on parallel clustering mining. Firstly, analyse the development stages of online learning resources and collect data on educational resources. Secondly, construct a network learning resource model and utilise parallel clustering to explore the clustering features of network learning resources. Finally, using the mined resource features, design network learning resource labels to achieve online allocation of network learning resources. The experimental results show that the accuracy of network learning resource allocation in this method is 98.2%, the accuracy of network learning resource allocation is 98.1%, and the reliability of allocation reaches 96.2%.

Keywords: parallel clustering mining; online allocation of learning resources; resource tags; education resource data.

DOI: 10.1504/IJBIDM.2025.143929

International Journal of Business Intelligence and Data Mining, 2025 Vol.26 No.1/2, pp.119 - 132

Received: 08 Nov 2023
Accepted: 07 May 2024
Published online: 14 Jan 2025 *

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