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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JCER</journal-id><journal-title-group><journal-title>Journal of Contemporary Educational Research</journal-title></journal-title-group><issn>2208-8466</issn><eissn>2208-8474</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jcer.v9i6.10901</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Intelligent Educational Administration Management System Based on Data Mining Technology</title><url>https://artdesignp.com/journal/JCER/9/6/10.26689/jcer.v9i6.10901</url><author>YangXiaofei</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>6</issue><history><date date-type="pub"><published-time>2025-06-30</published-time></date></history><abstract>With the gradual acceleration of information construction in colleges and universities, digital campus and smart campus have gradually become important means for colleges and universities to scientifically manage the campus. They have been applied to teaching, scientific research, student management, and other fields, improving the quality and efficiency of management. This paper mainly studies the intelligent educational administration management system based on data mining technology. Firstly, this paper introduces the application process of data mining technology, and builds an intelligent educational administration management system based on data mining technology. Then, this paper optimizes the application of the Apriori algorithm in educational administration management through transaction compression and frequent sampling. 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