Mining and Exploration of Credit Cards Data in UAE

Sarween Zaza, M. Al-Emran
{"title":"Mining and Exploration of Credit Cards Data in UAE","authors":"Sarween Zaza, M. Al-Emran","doi":"10.1109/ECONF.2015.57","DOIUrl":null,"url":null,"abstract":"Credit cards have become an essential element in the banking industry. Credit cards add a significant value for the banks. Mining credit cards can find interesting patterns among different variables that may be used in the future by the policy makers for building their future policy. In this study, we have investigated the credit card-holder's behavior in order to predict the market segmentation. An online questionnaire survey regarding credit card usage has been used for data collection. Two techniques have been applied on the collected data, Decision Trees and K-means through the use of training and testing sets. Results indicated how people are grouped based on their income which in turn will help in building the appropriate decision on which region needs to be targeted. Moreover, results revealed different work sectors for the credit card-holders and which type of credit card is used with regard to their income.","PeriodicalId":268471,"journal":{"name":"2015 Fifth International Conference on e-Learning (econf)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on e-Learning (econf)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECONF.2015.57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

Abstract

Credit cards have become an essential element in the banking industry. Credit cards add a significant value for the banks. Mining credit cards can find interesting patterns among different variables that may be used in the future by the policy makers for building their future policy. In this study, we have investigated the credit card-holder's behavior in order to predict the market segmentation. An online questionnaire survey regarding credit card usage has been used for data collection. Two techniques have been applied on the collected data, Decision Trees and K-means through the use of training and testing sets. Results indicated how people are grouped based on their income which in turn will help in building the appropriate decision on which region needs to be targeted. Moreover, results revealed different work sectors for the credit card-holders and which type of credit card is used with regard to their income.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
阿联酋信用卡数据的挖掘与探索
信用卡已经成为银行业的一个重要组成部分。信用卡为银行增加了可观的价值。对信用卡的挖掘可以在不同的变量中找到有趣的模式,这些模式将来可能会被政策制定者用于构建他们未来的政策。在本研究中,我们调查了信用卡持卡人的行为,以预测市场细分。关于信用卡使用情况的在线问卷调查已用于数据收集。通过使用训练集和测试集,在收集的数据上应用了两种技术:决策树和K-means。结果表明,人们如何根据收入分组,这反过来将有助于就需要针对哪个地区作出适当的决定。此外,调查结果还揭示了信用卡持有者的不同工作部门,以及他们使用的信用卡类型与他们的收入有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Future Educator Skills in the Digitization Era: Effects of Technological Development on Higher Education From a Dilapidated Blackboard to Creative Flash Videos: The Case of Training Teachers of Schools in Hebron Security Measures in a Keyless Quantum Communication Protocol Test of Information Technology (IT) - Self Efficacy and Online Learning Interaction Components on Student Retention: A Study of Synchronous Learning Environment The Effectiveness of the Flipped Classroom in Higher Education
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1