The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Turning telecommunications call details to churn prediction: a data mining approach
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Verbraken et al. (2012) and Neslin et al. (2006) proposed formulas for calculating the net profit using churn rate, CAC, CLV, fixed operating cost, and incentive cost.
“Verbraken, Thomas, Wouter Verbeke, and Bart Baesens.(2012) and Neslin, Scott A., et al. (2006) proposed formulas for calculating the net profit using churn rate, CAC, CLV, fixed operating cost, and incentive cost [54] [55].”
From A Survey on Churn Analysis in Various Business Domains (2020) · cites this paper as [54]
Citations
Cites
Quinlan, J. R. (1986) · Machine Learning · doi:10.1007/bf00116251 · Cited by 21,439
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A comparison of machine learning techniques for customer churn prediction
Vafeiadis, T., Diamantaras, K. I., Sarigiannidis, G., & Chatzisavvas, K. C. (2015) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2015.03.003 · Cited by 471
Verbeke, W., Dejaeger, K., Martens, D., Hur, J., & Baesens, B. (2012) · European Journal of Operational Research · doi:10.1016/j.ejor.2011.09.031 · Cited by 462
Wang, X., Zhao, K., & Street, N. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6834 · Cited by 182
A Survey on Churn Analysis in Various Business Domains
Ahn, J., Hwang, J., Kim, D., Choi, H., & Kang, S. (2020) · IEEE Access · doi:10.1109/access.2020.3042657 · Cited by 108
“(2002) have utilized RFM features in the telecommunication field as well [41].”
BackgroundMethodA SLR on Customer Dropout Prediction
Sobreiro, P., Martinho, D. D. S., Alonso, J. G., & Berrocal, J. (2022) · IEEE Access · doi:10.1109/access.2022.3146397 · Cited by 8
Metadata
- Authors
- Wei, C.-P., & Chiu, I.-T.
- Affiliations
- National Sun Yat-sen University (TW)
- Chunghwa Telecom (Taiwan) (TW)
- Corresponding author
- Wei, Chih-Ping
- ORCID
- Wei, Chih-Ping
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2002-08
- Volume
- 23
- Issue
- 2
- Pages
- 103-112
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2069300565
- Cited by
- 460
- References
- 1
- Citations by year
- 2026: 6 · 2025: 15 · 2024: 22 · 2023: 21 · 2022: 21 · 2021: 26 · 2020: 21 · 2019: 22 · 2018: 28 · 2017: 17 · 2016: 25 · 2015: 25 · 2014: 24 · 2013: 23 · 2012: 31
- FWCI
- 17.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
- Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- customer churn prediction, mobile communication, call detail records, customer retention, class imbalance, multi-classifier ensemble, mobile operators
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