6 July 2015 Application of text mining for customer evaluations in commercial banking
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Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 963120 (2015) https://doi.org/10.1117/12.2197178
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States
Abstract
Nowadays customer attrition is increasingly serious in commercial banks. To combat this problem roundly, mining customer evaluation texts is as important as mining customer structured data. In order to extract hidden information from customer evaluations, Textual Feature Selection, Classification and Association Rule Mining are necessary techniques. This paper presents all three techniques by using Chinese Word Segmentation, C5.0 and Apriori, and a set of experiments were run based on a collection of real textual data that includes 823 customer evaluations taken from a Chinese commercial bank. Results, consequent solutions, some advice for the commercial bank are given in this paper.
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Jing Tan, Jing Tan, Xiaojiang Du, Xiaojiang Du, Pengpeng Hao, Pengpeng Hao, Yanbo J. Wang, Yanbo J. Wang, } "Application of text mining for customer evaluations in commercial banking", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 963120 (6 July 2015); doi: 10.1117/12.2197178; https://doi.org/10.1117/12.2197178
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