{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,13]],"date-time":"2024-06-13T06:03:37Z","timestamp":1718258617196},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683461","type":"print"},{"value":"9781643683478","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:00:00Z","timestamp":1666051200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,18]]},"abstract":"<jats:p>In order to provide decision support for students\u2019 education management, a new student behavior analysis method based on the K-means algorithm and consumption data of campus smart card is proposed in this paper. An optimized Apriori algorithm is used to analyze the relationship between consumption behavior and academic performance. This method effectively provides management decision support for student managers, and improves management efficiency. This should improve the process of intelligent management.<\/jats:p>","DOI":"10.3233\/faia220376","type":"book-chapter","created":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T09:31:51Z","timestamp":1667208711000},"source":"Crossref","is-referenced-by-count":1,"title":["A New Student Behavior Analysis Method Based on K-Means Algorithm and Consumption Data of Campus Smart Card"],"prefix":"10.3233","author":[{"given":"Jinglong","family":"Zuo","sequence":"first","affiliation":[{"name":"College of Electronic Information Engineer, Guangdong University of Petrochemical Technology, Maoming, China"}]},{"given":"Marifel Grace C.","family":"Kummer","sequence":"additional","affiliation":[{"name":"School of Information Technology and Engineering and Graduate School, St.Paul University, Philippines"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining VIII"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220376","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T09:31:52Z","timestamp":1667208712000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220376"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,18]]},"ISBN":["9781643683461","9781643683478"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220376","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,18]]}}}