Telecom churn prediction and used techniques, datasets and performance measures: a review-Reference-Cited by-同舟云学术

Telecom churn prediction and used techniques, datasets and performance measures: a review

Published:2020-10-20 Issue:4 Volume:76 Page:613-630
ISSN:1018-4864
Container-title:Telecommunication Systems
language:en
Short-container-title:Telecommun Syst

Author:

Jain Hemlata^ORCID,Khunteta Ajay,Srivastava Sumit

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11235-020-00727-0.pdf

Reference59 articles.

1. Naz, N. A., Shoaib, U., & Shahzad Sarfraz, M. (2018). A review on customer churn prediction data mining modeling techniques. Indian Journal of Science and Technology, 11(27), 1–27.

2. Lazarov, V., & Capota, M. (2007). Churn prediction. Semantic Scholar. https://www.semanticscholar.org/paper/Churn-Prediction-Lazarov-Capota/dbf15b7c5f766ef9f84ba83127c626d79b2087b2.

3. Moayer, S., & Gardner, S. (2012). Integration of data mining within a strategic knowledge management framework. International Journal of Advanced Computer Science and Applications, 3(8), 67–72.

4. Pushpa, S. (2012). An efficient method of building the telecom social network for churn prediction. International Journal of Data Mining & Knowledge Management Process, 2(3), 31–39.

5. Hashmi, N., Butt, N. A., & Iqbal, M. (2013). Customer churn prediction in telecommunication a decade review and classification. IJCSI International Journal of Computer Science Issues, 10(5), 271.

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