Customer Churn Prediction Model using Data Mining techniques

被引：0
|
作者：
Mitkees, Ibrahim M. M. [1 ]
Badr, Sherif M. [2 ]
ElSeddawy, Ahmed Ibrahim Bahgat [3 ]
机构：
[1] Modern Acad, Dept Managment Informat Syst, Cairo, Egypt
[2] Modern Acad, Dept Comp Sci, Cairo, Egypt
[3] AASTMT, Dept Informat Syst, Cairo, Egypt
来源：
2017 13TH INTERNATIONAL COMPUTER ENGINEERING CONFERENCE (ICENCO) | 2017年
关键词：
Data Mining; Customer Churn; clustering; classification; association rule;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A big problem that encounters businesses, especially telecommunications business is 'customer churn'; this occurs when a customer decides to leave a company's landline business for another cable competitor. Therefore, our aim beyond this study to build a model that will predict churn customer through defining the customer's precise behaviors and attributes. We will use data mining techniques such as clustering, classification and association rule. The accuracy and preciseness of the technique used is so essential to the success of any retention attempting. After all, if the company is not aware of a customer who is about to leave their business; no proper action can be taken by that company towards that customer.
引用
收藏
页码：262 / 268
页数：7
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