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<p>In order to promote the model innovation of higher education management and student training mechanisms, this paper proposes data mining technology to assist the research of education management and training mechanisms. Using web crawler technology to obtain the required initial data for the study, data cleaning and conversion are carried out to ensure the accuracy of the results of the research and analysis in response to the problems of missing data, intermingled noise, and attribute redundancy in the initial data. Aiming at the slow efficiency and collapse of the traditional association rule algorithm in the face of massive data, the whale optimization algorithm is used to optimize the association rule algorithm for multi-objective optimization, and the optimized association rule algorithm is used to analyze the data of higher education management. The data showed that the Confidence=77.82% for the association rule poor grades in introductory courses=>poor grades in major courses, which indicates that the probability of students whose average grades in introductory courses are outside the 75th percentile and those whose average grades in significant classes are outside the 60.00th percentile is 77.82%. This study aids teachers and administrators in making scientific decisions to enhance teaching management, enhance teaching quality, and reduce costs associated with school operations.</p>
</abstract>

In order to promote the model innovation of higher education management and student training mechanisms, this paper proposes data mining technology to assist the research of education management and training mechanisms. Using web crawler technology to obtain the required initial data for the study, data cleaning and conversion are carried out to ensure the accuracy of the results of the research and analysis in response to the problems of missing data, intermingled noise, and attribute redundancy in the initial data. Aiming at the slow efficiency and collapse of the traditional association rule algorithm in the face of massive data, the whale optimization algorithm is used to optimize the association rule algorithm for multi-objective optimization, and the optimized association rule algorithm is used to analyze the data of higher education management. The data showed that the Confidence=77.82% for the association rule poor grades in introductory courses=>poor grades in major courses, which indicates that the probability of students whose average grades in introductory courses are outside the 75th percentile and those whose average grades in significant classes are outside the 60.00th percentile is 77.82%. This study aids teachers and administrators in making scientific decisions to enhance teaching management, enhance teaching quality, and reduce costs associated with school operations.

Artificial Intelligence Technology Facilitates Model Innovation in Higher Education Management and Student Training Mechanisms

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In order to promote the model innovation of higher education management and student training mechanisms, this paper proposes data mining technology to assist...

Artificial Intelligence Technology Facilitates Model Innovation in Higher Education Management and Student Training Mechanisms

Published Online: May 22, 2024

Page range: -

Received: Jan 25, 2024

Accepted: Apr 08, 2024

DOI: https://doi.org/10.2478/amns-2024-1173

Keywords
Whale optimization algorithm, Association rule algorithm, Web crawler, Data mining, Educational management

© 2024 Dangying Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artificial Intelligence Technology Facilitates Model Innovation in Higher Education Management and Student Training Mechanisms

Published Online: May 22, 2024

Page range: -

Received: Jan 25, 2024

Accepted: Apr 08, 2024

DOI: https://doi.org/10.2478/amns-2024-1173

KeywordsWhale optimization algorithm, Association rule algorithm, Web crawler, Data mining, Educational management

© 2024 Dangying Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Whale optimization algorithm, Association rule algorithm, Web crawler, Data mining, Educational management