Leveraging artificial intelligence for predictive customer churn modeling in telecommunications: a framework for enhanced customer relationship management. [PDF]
Abdelhady MG, Mohamed KA.
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Multimedia data-driven customer churn prediction using an enhanced extreme learning machine. [PDF]
Liu YW, Wang J, Liu C.
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Advanced customer churn prediction for a music streaming digital marketing service using attention graph-based deep learning approach. [PDF]
Cheng H, He J.
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Customer Churn Prediction Based on Sentiment Score [PDF]
In recent years, the telecommunications industry has witnessed intensified competition, wherein the expense associated with acquiring new consumers exceeds that of sustaining existing ones.
Al-Safi, Shadha
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Customer churn prediction model based on hybrid neural networks. [PDF]
Liu X, Xia G, Zhang X, Ma W, Yu C.
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning. [PDF]
Adiputra INM, Wanchai P, Lin PC.
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Application of GWO-attention-ConvLSTM model in customer churn prediction and satisfaction analysis in customer relationship management. [PDF]
Zhang H, Zhang W.
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A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model. [PDF]
He C, Ding CHQ.
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An integrated explainable AI framework with counterfactual optimization for decision support. [PDF]
Jahan N, Maua J, Rozario U, Shoaib HA.
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A new perspective on data leakage prevention and adaptive attention in telecom churn prediction. [PDF]
Le DT, Nguyen MT.
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