Profiling Television Watching Behavior Using Bayesian Hierarchical Joint Models for Time-to-Event and Count Data

Profiling Television Watching Behavior Using Bayesian Hierarchical Joint Models for Time-to-Event and Count Data

Customer churn prediction is a valuable task in many industries. In telecommunications it presents great challenges, given the high dimensionality of the data, and how difficult it is to identify underlying frustration signatures, which may represent an important driver regarding future churn behavi...

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Bibliographic Details
Main Authors: Rafael A. Moral, Zhi Chen, Shuai Zhang, Sally McClean, Gabriel R. Palma, Brahim Allan, Ian Kegel
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Bayesian modelling
big data
churn prediction
clustering
dimensionality reduction
frustration signatures
Online Access:https://ieeexplore.ieee.org/document/9923761/

Internet

https://ieeexplore.ieee.org/document/9923761/

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