Abstract
This work surveys the research contributions of the last decade to the prediction of customer churn and adds a perspective toward what is yet to be reached. The main objective of this article is to report on (1) the methods and algorithms studied, the evaluation metrics adopted, and the results achieved, (2) the data used, and (3) the issues and limitations identified. Furthermore, the work highlights the gaps in the current literature and suggests a direction for future research.
Lingua originale | English |
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pagine (da-a) | N/A-N/A |
Numero di pagine | 15 |
Rivista | SN Computer Science |
Volume | 5 |
Numero di pubblicazione | 4 |
DOI | |
Stato di pubblicazione | Pubblicato - 2024 |
Keywords
- Causal inference
- Churn prediction
- Machine learning techniques
- Telecom customer churn