Noise-augmented contrastive learning with attention for knowledge-aware collaborative recommendation

Abstract Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, Graph Convolutional Network (GCN) and Graph Attention Network (GAT) based model has gradually become the theme of Collaborative Knowledge Graph (CKG). However, recommender systems encounter long-tail...

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Principais autores:	Wanyi Gu, Hua Xu, Xiang Peng, Ning Rao, Huali Zhu
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Nature Portfolio 2025-10-01
סדרה:	Scientific Reports
נושאים:	Recommendation Contrastive learning Knowledge graph Noise-based augmentation Graph attention network
גישה מקוונת:	https://doi.org/10.1038/s41598-025-17640-8
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!