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Cost-Sensitive-Data Preprocessing for Mining Customer Relationship Management Databases

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6 Author(s)
Junfeng Pan ; Hong Kong Univ. of Sci. & Technol., Kowloon ; Qiang Yang ; Yiming Yang ; Lei Li
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A staged-framework for data preprocessing has been developed to support data mining and help service providers identify customers who might switch to a competitor. The framework pushes the cost sensitivity and data imbalance of customer retention data into the data preprocessing itself. Tests using data set from the ACM KDD Cup 1998 showed that the framework outperformed the winner of that data mining and knowledge discovery competition. The framework has also been incorporated into a software system, called ED-Money. To demonstrate the framework's ability to predict customer attrition with high accuracy, it was applied to some benchmark data and to a real customer attrition data set from a large Chinese mobile telecommunications company

Published in:

Intelligent Systems, IEEE  (Volume:22 ,  Issue: 1 )