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Incorporating textual information in customer churn prediction models based on a convolutional neural network

Citations

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Cited by:

  1. Li, Qiang & Li, Yuangang & Jing, Ranzhe, 2025. "A variant bagging forecasting framework for customer churn in airline," Journal of Air Transport Management, Elsevier, vol. 125(C).
  2. Liu, Zhenkun & Zhang, Ying & Abedin, Mohammad Zoynul & Wang, Jianzhou & Yang, Hufang & Gao, Yuyang & Chen, Yinghao, 2024. "Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
  3. Abedin, Mohammad Zoynul & Hajek, Petr & Sharif, Taimur & Satu, Md. Shahriare & Khan, Md. Imran, 2023. "Modelling bank customer behaviour using feature engineering and classification techniques," Research in International Business and Finance, Elsevier, vol. 65(C).
  4. Chen, Yan & Zhang, Lei & Zhao, Yulu & Xu, Bing, 2022. "Implementation of penalized survival models in churn prediction of vehicle insurance," Journal of Business Research, Elsevier, vol. 153(C), pages 162-171.
  5. David Hason Rudd & Huan Huo & Md. Rafiqul Islam & Guandong Xu, 2023. "Churn Prediction via Multimodal Fusion Learning: Integrating Customer Financial Literacy, Voice, and Behavioral Data [Prédiction du churn par apprentissage fusionné multimodal : intégration de la littératie financière, des données vocales et compo," Post-Print hal-04320145, HAL.
  6. De Caigny, Arno & Coussement, Kristof & Hoornaert, Steven & Meire, Matthijs, 2025. "Life event-based marketing using AI," Journal of Business Research, Elsevier, vol. 193(C).
  7. Liu, Zhenkun & Jiang, Ping & De Bock, Koen W. & Wang, Jianzhou & Zhang, Lifang & Niu, Xinsong, 2024. "Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  8. Louis Geiler & Séverine Affeldt & Mohamed Nadif, 2022. "A survey on machine learning methods for churn prediction," Post-Print hal-03824873, HAL.
  9. Gómez-Vargas, Nuria & Maldonado, Sebastián & Vairetti, Carla, 2025. "A predict-and-optimize approach to profit-driven churn prevention," European Journal of Operational Research, Elsevier, vol. 324(2), pages 555-566.
  10. Christopher Gerling & Stefan Lessmann, 2023. "Multimodal Document Analytics for Banking Process Automation," Papers 2307.11845, arXiv.org, revised Nov 2023.
  11. Christophe Schalck & Meryem Yankol‐Schalck, 2026. "Innovative Techniques to Predict Churn in the French Insurance Industry: Integration of Machine Learning With the Grabit Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 652-669, March.
  12. Philipp Borchert & Kristof Coussement & Arno de Caigny & Jochen de Weerdt, 2023. "Extending business failure prediction models with textual website content using deep learning," Post-Print hal-03976762, HAL.
  13. Gary Mena & Kristof Coussement & Koen W. Bock & Arno Caigny & Stefan Lessmann, 2024. "Exploiting time-varying RFM measures for customer churn prediction with deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 765-787, August.
  14. Christopher Gerling & Stefan Lessmann, 2024. "Leveraging AI and NLP for Bank Marketing: A Systematic Review and Gap Analysis," Papers 2411.14463, arXiv.org.
  15. Seema & Gaurav Gupta, 2024. "Development of fading channel patch based convolutional neural network models for customer churn prediction," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(1), pages 391-411, January.
  16. Feng, Yi & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Marra, Marianna & Guo, Yihan, 2024. "Enhancing e-commerce customer churn management with a profit- and AUC-focused prescriptive analytics approach," Journal of Business Research, Elsevier, vol. 184(C).
  17. Ahn, Jungkyu & Ahn, Yongkil, 2023. "What drives the TIPS–Treasury bond mispricing?," Journal of Empirical Finance, Elsevier, vol. 74(C).
  18. Muhammad Zafran Muhammad Zaly Shah & Anazida Zainal & Taiseer Abdalla Elfadil Eisa & Hashim Albasheer & Fuad A. Ghaleb, 2023. "A Semisupervised Concept Drift Adaptation via Prototype-Based Manifold Regularization Approach with Knowledge Transfer," Mathematics, MDPI, vol. 11(2), pages 1-30, January.
  19. Arno Caigny & Kristof Coussement & Matthijs Meire & Steven Hoornaert, 2025. "Investigating the impact of undersampling and bagging: an empirical investigation for customer attrition modeling," Annals of Operations Research, Springer, vol. 346(3), pages 2401-2421, March.
  20. Borchert, Philipp & Coussement, Kristof & De Caigny, Arno & De Weerdt, Jochen, 2023. "Extending business failure prediction models with textual website content using deep learning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 348-357.
  21. K. Coussement & K. W. Bock & S. Geuens, 2022. "A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer," Annals of Operations Research, Springer, vol. 315(2), pages 671-694, August.
  22. Lewlisa Saha & Hrudaya Kumar Tripathy & Tarek Gaber & Hatem El-Gohary & El-Sayed M. El-kenawy, 2023. "Deep Churn Prediction Method for Telecommunication Industry," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
  23. G. Mena & K. Coussement & K. de Bock & A. de Caigny & S. Lessmann, 2024. "Exploiting Time-Varying RFM Measures for Customer Churn Prediction with Deep Neural Networks," Post-Print hal-04680677, HAL.
  24. Ghazaleh Motamedi & Alireza Sheikh & Alireza Hashemi Golpayegani & Samira Khodabandehlou, 2026. "A hybrid approach for customer churn prediction and prevention in tourism," Information Technology & Tourism, Springer, vol. 28(1), pages 1-36, June.
  25. Atin Aboutorabi & Ga'etan de Rassenfosse, 2024. "Nowcasting R&D Expenditures: A Machine Learning Approach," Papers 2407.11765, arXiv.org.
  26. Lamrhari, Soumaya & Ghazi, Hamid El & Oubrich, Mourad & Faker, Abdellatif El, 2022. "A social CRM analytic framework for improving customer retention, acquisition, and conversion," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
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