Denoising Long-Tail Augmented Contrastive Network for Multi-Behavior Recommendation

Denoising Long-Tail Augmented Contrastive Network for Multi-Behavior Recommendation

Recommendation systems in multi-behavior recommendation systems integrate various user behavior data (e.g., favorites, cart) for representation learning, often alleviating the problem of data sparsity and enabling a more comprehensive user profile compared to traditional recommendation systems. Rece...

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Bibliographic Details
Main Authors: Jinle He, Chengyong Yang, Jiayi Liu, Jianlin Cheng
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Collaborative filtering
multi-behavior recommendation
graph neural network
long-tail recommendation
graph augmentation
Online Access:https://ieeexplore.ieee.org/document/10752504/
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https://ieeexplore.ieee.org/document/10752504/

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