A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering
- DOI
- 10.1038/s41598-026-53220-0
- Published
- 2026-05-28
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-53220-0,
title = {A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering},
author = {Samia Ibrahim and BenBella S. Tawfik and Mohamed Abdallah Makhlouf and B. Hafiz},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-53220-0},
url = {https://doi.org/10.1038/s41598-026-53220-0}
}RIS
TY - JOUR TI - A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering AU - Samia Ibrahim AU - BenBella S. Tawfik AU - Mohamed Abdallah Makhlouf AU - B. Hafiz PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-53220-0 UR - https://doi.org/10.1038/s41598-026-53220-0 ER -
APA
Ibrahim, S., Tawfik, B. S., Makhlouf, M. A., & Hafiz, B. (2026). A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering. Scientific Reports. https://doi.org/10.1038/s41598-026-53220-0
Source records
- crossref · retrieved 2026-11-10T13:42:25.991Z