NAH-GNN: A graph-based framework for multi-behavior and high-hop interaction recommendation

With the growing demand for personalized marketing, recommender systems have become essential tools to help users quickly discover products or content that match their interests. However, traditional recommendation methods face significant limitations in handling complex user behaviors and sparse da...

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Bibliographic Details
Published in:PloS one 2025-04, Vol.20 (4), p.e0321419
Main Author: Tan, Guangzhu
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Biology and Life Sciences
Computer and Information Sciences
Engineering and Technology
Humans
Marketing - methods
Neural networks
Neural Networks, Computer
Personal preferences (Social sciences)
Physical Sciences
Research and Analysis Methods
Social networks
Social Sciences
Citations: Items that this one cites
Online Access:Get full text
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