Article: Online education resource integration method for painting teaching of art majors based on cloud platform Journal: International Journal of Computational Systems Engineering (IJCSYSE) 2025 Vol.9 No.5 pp.1 - 10 Abstract: A method for integrating educational resource data is proposed to address the issue of redundant and low utilisation of educational resources in current cloud platforms. Firstly, the PMI algorithm is combined with Simhash algorithm to construct the PMI Simhash algorithm. Secondly, it is combined with mixed similarity to establish a BSM multimodal data matching model. Finally, an unsupervised self-learning entity matching algorithm based on Euclidean locally sensitive hashing algorithm and correlation vector machine is proposed, and a data integration method for cloud platform educational resources is constructed. During the test, the precision of BSM model was 0.953, recall was 0.962, F1 was 0.929, overall was 90.72%, and AUC value was 0.971. The precision of US-EM model was 97.78%, recall was 94.62%, F1 was 95.14%, and AUC value was 0.968. The above data validates the effectiveness of the research method and indicates that the study has positive implications for online education. Inderscience Publishers - linking academia, business and industry through research

Title: Online education resource integration method for painting teaching of art majors based on cloud platform

Authors: Muchao Zhang

Addresses: Academy of Fine Arts, Nanjing Xiaozhuang University, 211171, Nanjing, China

Abstract: A method for integrating educational resource data is proposed to address the issue of redundant and low utilisation of educational resources in current cloud platforms. Firstly, the PMI algorithm is combined with Simhash algorithm to construct the PMI Simhash algorithm. Secondly, it is combined with mixed similarity to establish a BSM multimodal data matching model. Finally, an unsupervised self-learning entity matching algorithm based on Euclidean locally sensitive hashing algorithm and correlation vector machine is proposed, and a data integration method for cloud platform educational resources is constructed. During the test, the precision of BSM model was 0.953, recall was 0.962, F1 was 0.929, overall was 90.72%, and AUC value was 0.971. The precision of US-EM model was 97.78%, recall was 94.62%, F1 was 95.14%, and AUC value was 0.968. The above data validates the effectiveness of the research method and indicates that the study has positive implications for online education.

Keywords: cloud platform; art major; painting teaching; online education; resource integration.

DOI: 10.1504/IJCSYSE.2025.144358

International Journal of Computational Systems Engineering, 2025 Vol.9 No.5, pp.1 - 10

Received: 14 Jun 2023
Accepted: 03 Jul 2024
Published online: 10 Feb 2025 *

Title: Online education resource integration method for painting teaching of art majors based on cloud platform

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