K Nearest Sequence Method and Its Application to Churn Prediction

Author:

Ruta Dymitr,Nauck Detlef,Azvine Ben

Publisher

Springer Berlin Heidelberg

Reference7 articles.

1. Furnas, G.: Framing the wireless market. The Future of Wireless,WSA News:Bytes 17(11), 4–6 (2003)

2. Yan, L., Miller, D.J., Mozer, M.C., Wolniewicz, R.: Improving prediction of customer behaviour in non-stationary environments. In: Proc. of Int. Joint Conf. on Neural Networks, pp. 2258–2263 (2001)

3. Morgan, M.: Unearthing the customer: data mining is no longer the preserve of mathematical statisticians. Marketeers can also make a real, practical use of it (Revenue-Generating Networks). Telecommunications International (May 2003)

4. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern classification. John Wiley & Sons, Chichester (2001)

5. Mozer, M., Wolniewicz, R.H., Grimes, D.B., Johnson, E., Kaushansky, H.: Churn Reduction in the Wireless Industry. In: Neural Information Processing Systems Conf., pp. 935–941 (1999)

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