Deep Learning as a Vector Embedding Model for Customer Churn

Author:

Cenggoro Tjeng Wawan,Wirastari Raditya Ayu,Rudianto Edy,Mohadi Mochamad Ilham,Ratj Dinne,Pardamean Bens

Publisher

Elsevier BV

Subject

General Engineering

Reference37 articles.

1. Yan, L., Fassino, M., Baldasare, P. Predicting customer behavior via calling links. In: Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.; vol. 4. IEEE; 2005, p. 2555–2560.

2. Mattison, R. The telco churn management handbook. Lulu. com; 2006.

3. Applying data mining to customer churn prediction in an internet service provider;Khan;International Journal of Computer Applications,2010

4. Predicting customer churn in mobile telephony industry using probabilistic classifiers in data mining;Kirui;International Journal of Computer Science Issues (IJCSI),2013

5. An improved version of texture-based foreground segmentation: block-based adaptive segmenter;Muchtar;Procedia Computer Science,2018

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1. ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry;IEEE Access;2024

2. A deep multimodal autoencoder-decoder framework for customer churn prediction incorporating chat-GPT;Multimedia Tools and Applications;2023-12-11

3. Ensemble classification using balanced data to predict customer churn: a case study on the telecom industry;Multimedia Tools and Applications;2023-10-19

4. A Review on Machine Learning-Based Customer Churn Prediction in the Telecom Industry;2023 9th International Conference on Control, Decision and Information Technologies (CoDIT);2023-07-03

5. Customer Segmentation Analysis leveraging Machine Learning Algorithms;2023 IEEE International Conference on Contemporary Computing and Communications (InC4);2023-04-21

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