MB-AGCL: multi-behavior adaptive graph contrast learning for recommendation

Abstract Graph Convolutional Networks (GCNs) have achieved remarkable success in recommendation systems by leveraging higher-order neighborhoods. In recent years, multi-behavior recommendation has addressed the challenges of data sparsity and cold start problems to some extent. However, the introduc...

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Bibliographic Details

Published in:	Complex & Intelligent Systems
Main Authors:	Xiaowen lv, Yiwei Zhao, Zhihu Zhou, Yifeng Zhang, Yourong Chen
Format:	Article
Language:	English
Published:	Springer 2025-04-01
Subjects:	Recommendation Contrastive learning Graph representation Self-supervised learning
Online Access:	https://doi.org/10.1007/s40747-025-01880-2