Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms-Reference-Cited by-同舟云学术

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Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms

Published:2021-11 Issue:6 Volume:58 Page:102706
ISSN:0306-4573
Container-title:Information Processing & Management
language:en
Short-container-title:Information Processing & Management

Author:

Pustokhina Irina V.,Pustokhin Denis A.,RH Aswathy,Jayasankar T.,Jeyalakshmi C.,Díaz Vicente García,Shankar K.

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference28 articles.

1. Leveraging unstructured call log data for customer churn prediction;Vo;Knowledge-Based Systems,2021

2. Financial crisis prediction model using ant colony optimization;Uthayakumar;International Journal of Information Management,2020

3. Giant fight: Customer churn prediction in traditional broadcast industry;Li;Journal of Business Research,2021

4. Intelligent data analysis approaches to churn as a business problem: A survey;García;Knowl. Inf. Syst.,2017

5. Why you should stop predicting customer churn and start using uplift models;Devriendt;Information Sciences,2021

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5. A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners;IEEE Access;2024

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