Contrastive learning on high-order noisy graphs for collaborative recommendation

Abstract The graph-based collaborative filtering method has shown significant application value in recommendation systems, as it models user-item preferences by constructing a user-item interaction graph. However, existing methods face challenges related to data sparsity in practical applications. A...

Full description

Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Jiahao Wang, Qingshuai Wang, Noor Farizah Ibrahim, Zurinahni Zainol
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-10-01
Subjects:	Graph neural networks Contrastive learning Recommender systems Collaborative filtering
Online Access:	https://doi.org/10.1038/s41598-025-15890-0