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The Design and Implementation of Telecom Customer Clustering

Author: KangHongGang
Tutor: YangWenChuan
School: Beijing University of Posts and Telecommunications
Course: Software Engineering
Keywords: Data Mining Telecommunications Customer segmentation Thematic analysis
CLC: F626
Type: Master's thesis
Year: 2009
Downloads: 37
Quote: 0
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Abstract


Data mining in recent years, accompanied by the development of artificial intelligence and database technology and the emergence of a new and emerging technologies . Its core function is from huge data sets or data warehouse to obtain useful information for business analysis and processing of complex data relationships . With the increasing competition in the telecommunications market , operators generally started to \In recent years, data mining technology with its powerful data analysis capabilities are widely applied to the telecom operator customers management. Currently , telecom operators are facing fierce competition in the market , intensified competition for customers , every business there is the problem of customer churn . The traditional sense, to retain a customer needs to fight a new user cost is the cost of 1/ 5 , in particular, the market for the remaining customers increasingly sparse communications market, reduce churn means reduced costs with less profit drain, this point has been as widely accepted carriers . But the problem is that when operators are facing a flood of customer information , how should be able to extract the useful information to determine the status of customer churn or tendencies. In this case, the data provided by the data mining exploration capacity has been fully exploited. This thesis is based on CRISP-DM methodology , on the \market segmentation , the marketer needs based on the difference between the customer , the overall market is divided into a number of consumer groups in the market segment , and a brief description of data mining in customer churn analysis management process . The main contents of this paper consists of three parts : 1, the data mining technology introduction ; 2 , the telecommunications industry customer relationship system characteristic analysis ; 3, using the CRISP-DM method for a telecommunications customer base cluster analysis .

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