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高职院校奖助金推荐系统研究及资助对象行为分析

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随着高校数字化建设的不断深入,如何从海量教育数据中挖掘出与奖助金评判相关的数据及评判方法值得深思.以学生在校成绩、消费情况、贫困程度、社团活动、奖惩及竞赛等数据为基础,设计奖助金推荐系统,以决策树算法为依托,对学生的奖助金评判进行分析研究,并对获评对象在校活动进行监督分析,结果表明奖助金推荐系统可以为高校决策提供管理依据.
Research on the Grant Recommendation System in Higher Vocational Colleges and the Behavior Analysis of the Recipients
With the continuous deepening of digital construction in colleges and universities, it is worth pondering how to dig out the data and evaluation methods related to grant evaluation from massive educational data. Based on the data of students' academic performance, consumption, poverty level, club activities, rewards and punishments, and competitions, the grant recommendation system is designed. Based on decision tree algorithm, the evaluation of students' grants is analyzed and studied, and the activities of the recipients are supervised and analyzed. The results show that the grant recommendation system can provide management basis for universities' decision-making.

grantrecommendation systemdecision tree algorithmbehavior analysis

严志、王涛

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长沙民政职业技术学院,湖南长沙 410004

奖助金 推荐系统 决策树算法 行为分析

湖南省教育厅科研项目(2022)湖南省教育信息技术研究课题(2023)

22C1427HNETR23150

2024

湖南邮电职业技术学院学报
长江通信职业技术学院

湖南邮电职业技术学院学报

影响因子:0.424
ISSN:2095-7661
年,卷(期):2024.23(1)
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