电信行业属性选择与客户流失预测

V. Umayaparvathi, K. Iyakutti
{"title":"电信行业属性选择与客户流失预测","authors":"V. Umayaparvathi, K. Iyakutti","doi":"10.1109/SAPIENCE.2016.7684171","DOIUrl":null,"url":null,"abstract":"In this competitive world, business is becoming highly saturated. Especially, the field of telecommunication faces complex challenges due to a number of vibrant competitive service providers. Therefore, it has become very difficult for them to retain existing customers. Since the cost of acquiring new customers is much higher than the cost of retaining the existing customers, it is the time for the telecom industries to take necessary steps to retain the customers to stabilize their market value. This paper explores the application of data mining techniques in predicting the likely churners and attribute selection on identifying the churn. It also compares the efficiency of several classifiers and lists their performances for two real telecom datasets.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Attribute selection and Customer Churn Prediction in telecom industry\",\"authors\":\"V. Umayaparvathi, K. Iyakutti\",\"doi\":\"10.1109/SAPIENCE.2016.7684171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this competitive world, business is becoming highly saturated. Especially, the field of telecommunication faces complex challenges due to a number of vibrant competitive service providers. Therefore, it has become very difficult for them to retain existing customers. Since the cost of acquiring new customers is much higher than the cost of retaining the existing customers, it is the time for the telecom industries to take necessary steps to retain the customers to stabilize their market value. This paper explores the application of data mining techniques in predicting the likely churners and attribute selection on identifying the churn. It also compares the efficiency of several classifiers and lists their performances for two real telecom datasets.\",\"PeriodicalId\":340137,\"journal\":{\"name\":\"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAPIENCE.2016.7684171\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAPIENCE.2016.7684171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

摘要

在这个竞争激烈的世界里,商业正变得高度饱和。特别是,由于许多充满活力的竞争服务提供商,电信领域面临着复杂的挑战。因此,他们很难留住现有的客户。由于获得新客户的成本远远高于保留现有客户的成本,电信行业是时候采取必要的措施来保留客户,以稳定其市场价值。本文探讨了数据挖掘技术在客户流失预测中的应用,以及在客户流失识别中的属性选择。它还比较了几种分类器的效率,并列出了它们在两个真实电信数据集上的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attribute selection and Customer Churn Prediction in telecom industry
In this competitive world, business is becoming highly saturated. Especially, the field of telecommunication faces complex challenges due to a number of vibrant competitive service providers. Therefore, it has become very difficult for them to retain existing customers. Since the cost of acquiring new customers is much higher than the cost of retaining the existing customers, it is the time for the telecom industries to take necessary steps to retain the customers to stabilize their market value. This paper explores the application of data mining techniques in predicting the likely churners and attribute selection on identifying the churn. It also compares the efficiency of several classifiers and lists their performances for two real telecom datasets.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信