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Research on Credit Card Customer Segmentation Model Based on Associative Classification

Author: WangNa
Tutor: ZuoChunHua
School: Zhejiang Technology and Business University
Course: Management Science and Engineering
Keywords: Credit card Associative Classification Relevance Customer Segmentation
CLC: F224
Type: Master's thesis
Year: 2010
Downloads: 136
Quote: 1
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Abstract


With the increased competition in the credit card market, customer diversification characteristics presented, the mode of operation of the domestic banks have been gradually transition to the international customer-centric model, banks to maintain a leading position in the market must take the initiative to conduct customer segmentation. Most traditional customer segmentation based on experience or simple statistical methods can not meet the growing amount of data and complex analytical needs of the business development. Appear based on data mining technology classification method to solve complex customer segmentation issues under the massive data provide new solutions, but also provides an effective tool targeted marketing segmentation based on credit card customers. In this paper, based on research at home and abroad based on the bank in the presence of a large number of credit card data, associative classification algorithm of the bank's credit card customers data mining, customer segmentation, targeted marketing, thereby improving customer satisfaction and competitive value. The main contents are as follows: associative classification algorithm in-depth study, in particular, a detailed analysis of classical algorithm and objective comparison of to establish theoretical premise for associative classification improved algorithm proposed in this paper. Second, to build the index system for credit card customer segmentation. Through the consumption behavior of customers in the process of using the credit card, and taking into account the implied value of user behavior, to conduct a comprehensive analysis of the three dimensions of customer behavior and customer lifetime value from the customer's personal characteristics, On this basis, constructed the index system for credit card customer segmentation, customer segmentation as basis. Third, associative classification algorithm based on the correlation ACBC. First, Relevance CM greedy algorithm combination, confidence Relevance replace traditional as rule quality assessment standards, delete irrelevant or weakly related rules in the rule generation step directly. Then, using the rules of priority Sort pruning strategies and database coverage pruning strategy combining select the appropriate set of rules from the initial classification rules set to build a classifier. Finally, the use of classification and prediction of the classifier on the test data set. Proved by experiments, ACBC algorithm has better classification results, to reduce the computing time and storage space occupied. Fourth, the proposed classification algorithm based on the correlation associated bank credit card customer segmentation model (ACSM). Bank customer data data sources using ACBC algorithm as the key technology to calculate the degree of correlation between the frequent attribute set and class labels breakdown of the credit card customers, and in accordance with the classification results marketing model and personality marketing means.

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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