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https://doi.org/10.1023/A:1006676015154
Title: | Customer retention via data mining | Authors: | Ng, K. Liu, H. |
Keywords: | Customer retention Data mining Deviation analysis Feature selection Multiple level association rules |
Issue Date: | 2000 | Citation: | Ng, K., Liu, H. (2000). Customer retention via data mining. Artificial Intelligence Review 14 (6) : 569-590. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1006676015154 | Abstract: | "Customer Retention" is an increasingly pressing issue in today's ever-competitive commercial arena. This is especially relevant and important for sales and services related industries. Motivated by a real-world problem faced by a large company, we proposed a solution that integrates various techniques of data mining, such as feature selection via induction, deviation analysis, and mining multiple concept-level association rules to form an intuitive and novel approach to gauging customer loyalty and predicting their likelihood of defection. Immediate action triggered by these "early-warnings" resulting from data mining is often the key to eventual customer retention. | Source Title: | Artificial Intelligence Review | URI: | http://scholarbank.nus.edu.sg/handle/10635/39270 | ISSN: | 02692821 | DOI: | 10.1023/A:1006676015154 |
Appears in Collections: | Staff Publications |
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