[1]龚黎旰,顾坤,明心铭,等.基于校园一卡通大数据的高校学生消费行为分析[J].深圳大学学报理工版,2020,37(增刊1):150-154.[doi:10.3724/SP.J.1249.2020.99150]
 GONG Ligan,GU Kun,MING Xinming,et al.Analysis of college students’ consumption behavior based on campus card data[J].Journal of Shenzhen University Science and Engineering,2020,37(增刊1):150-154.[doi:10.3724/SP.J.1249.2020.99150]
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基于校园一卡通大数据的高校学生消费行为分析()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第37卷
期数:
2020年增刊1
页码:
150-154
栏目:
教育大数据技术与应用
出版日期:
2020-11-20

文章信息/Info

Title:
Analysis of college students’ consumption behavior based on campus card data
文章编号:
202099027
作者:
龚黎旰1顾坤2明心铭3徐明1秦斌1
1)深圳大学信息中心,广东深圳 518060
2)深圳大学电子与信息工程学院,广东深圳 518060
3)深圳大学机电与控制工程学院,广东深圳 518060
Author(s):
GONG Ligan1 GU Kun2 MING Xinming3 XU Ming1 and QIN Bin1
1) Information Center, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
2) College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
3) College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
关键词:
计算机应用校园一卡通消费行为分析教育大数据教育数据挖掘Spark
Keywords:
computer application campus card consumer behavior analysis educational big data educational data mining Spark
分类号:
TP315
DOI:
10.3724/SP.J.1249.2020.99150
文献标志码:
A
摘要:
为进一步提升高校的智慧管理水平,以某高校校园一卡通消费记录为数据基础,利用大数据和数据挖掘技术对其展开分析研究,挖掘学生消费行为背后的隐藏信息.通过对提取数据进行预处理和特征工程,统计分析学生的消费水平和消费习惯;采用聚类算法圈选出具有不同消费行为的学生群体,深度分析不同群体的消费组成结构和消费行为特征;通过构建学生共现网络,研究学生社交关系并发现学生群体中的孤独者.结果表明,利用聚类算法辅助学校资助部门开展精准助学工作是可行的,构建学生共现网络也为高校心理辅导工作提供一定参考依据.
Abstract:
In order to further improve the intelligent management level of universities, we use big data and data mining technology to analyze the data including a university’s campus card consumption records. Firstly, through the preprocessing and feature engineering of the extracted data, we analyze students’ consumption level, consumption habits and other laws. Then, we cluster students into different groups with different consumption behaviors, and analyze the consumption structure and consumption behavior characteristics for the different groups in depth. Finally, by constructing a student co-occurrence network, we study the social relationships of students and find the lonely persons. The experimental results show that our clustering algorithm can assist the accurate student aid work, and the construction of the student co-occurrence network can also provide a certain reference for the psychological counseling work.

参考文献/References:

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备注/Memo

备注/Memo:
Received:2020-09-30
Foundation:Postgraduate Education Reform Project of Shenzhen University (860-000001050503)
Corresponding author:Engineer GONG Ligan. E-mail:gonglg@szu.edu.cn
Citation:GONG Ligan, GU Kun, MING Xinming, et al. Analysis of college students’ consumption behavior based on campus card data [J]. Journal of Shenzhen University Science and Engineering, 2020, 37(Suppl.1): 150-154.(in Chinese)
基金项目:深圳大学研究生教育改革基金资助项目 (860-0000010 50503)
作者简介:龚黎旰(1971—),深圳大学工程师.研究方向:信息技术.E-mail:gonglg@szu.edu.cn
引文:龚黎旰,顾坤,明心铭,等. 基于校园一卡通大数据的高校学生消费行为分析[J]. 深圳大学学报理工版,2020,37(增刊1):150-154.
更新日期/Last Update: 2020-11-26