User Behavior Sequence Mining via Graph Neural Networks for Customer Lifetime Value Prediction and Precision Marketing Strategy Formulation

Customer Lifetime Value (CLV) prediction is a core task in retail and e-commerce, enabling enterprises to optimize resource allocation and formulate precision marketing strategies. Traditional CLV prediction methods rely heavily on manual feature engineering and fail to fully capture the sequential...

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Détails bibliographiques

Auteur principal:	Yalin Pang
Format:	Artigo
Langue:	Inglês
Publié:	Tamkang University Press 2026-03-01
Collection:	Journal of Applied Science and Engineering
Sujets:	user behavior sequence graph neural networks customer lifetime value precision marketing temporal attention heterogeneous graph modeling
Accès en ligne:	http://jase.tku.edu.tw/articles/jase-202608-31-058
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