An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry [PDF]
PeerJ Computer Science, 2022 Mobile communication has become a dominant medium of communication over the past two decades. New technologies and competitors are emerging rapidly and churn prediction has become a great concern for telecom companies.
Syed Fakhar Bilal +4 more
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Customer churn prediction for telecommunication industry: A Malaysian Case Study [version 1; peer review: 2 approved] [PDF]
F1000Research, 2021 Background: Customer churn is a term that refers to the rate at which customers leave the business. Churn could be due to various factors, including switching to a competitor, cancelling their subscription because of poor customer service, or ...
Nurulhuda Mustafa +2 more
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Advanced customer churn prediction for a music streaming digital marketing service using attention graph-based deep learning approach [PDF]
Scientific ReportsCustomer churn poses a persistent threat to the sustainability of music streaming platforms, where user disengagement often occurs unpredictably. Most existing churn prediction methods fail to integrate relational dependencies among users or address the ...
Haiyan Cheng, Jie He
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Behavioral attributes and financial churn prediction [PDF]
EPJ Data Science, 2018 Customer retention is crucial in a variety of businesses as acquiring new customers is often more costly than keeping the current ones. As a consequence, churn prediction has attracted great attention from both the business and academic worlds ...
Erdem Kaya +5 more
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Churn prediction on huge telecom data using hybrid firefly based classification
Egyptian Informatics Journal, 2017 Churn prediction in telecom has become a major requirement due to the increase in the number of telecom providers. However due to the hugeness, sparsity and imbalanced nature of the data, churn prediction in telecom has always been a complex task.
Ammar A.Q. Ahmed, D. Maheswari
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Churn prediction of mobile and online casual games using play log data. [PDF]
PLoS ONE, 2017 Internet-connected devices, especially mobile devices such as smartphones, have become widely accessible in the past decade. Interaction with such devices has evolved into frequent and short-duration usage, and this phenomenon has resulted in a pervasive
Seungwook Kim +3 more
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Integrating generative AI and machine learning classifiers for solving heterogenous MCGDM: a case of employee churn prediction [PDF]
Scientific ReportsEmployee churn is a critical issue for companies and organizations, as it directly impacts productivity, efficiency, and overall operational success.
Hagar G. Abu-Faty +3 more
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Enhancing customer retention in telecom industry with machine learning driven churn prediction [PDF]
Scientific ReportsCustomer churn remains a critical concern for businesses, highlighting the significance of retaining existing customers over acquiring new ones. Effective prediction of potential churners aids in devising robust retention policies and efficient customer ...
Alisha Sikri +3 more
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Combining predictive accuracy and interpretability: a data-driven approach to telecom churn analysis [PDF]
Scientific ReportsAcquiring consumers is a challenge in the telecom industry since it reduces profits and slows growth. Customer churn prediction remains a pivotal challenge for telecommunications companies seeking to retain subscribers and sustain profitability in highly
Pankaj Hooda +4 more
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Churn Prediction for High-Value Players in Freemium Mobile Games: Using Random Under-Sampling [PDF]
Statistika: Statistics and Economy Journal, 2022 Many game development companies use game data analysis for mining insights about users' behaviour and possible product growth. One of the most important analysis tasks for game development is user churn prediction.
Guan-Yuan Wang
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