AsGCL: Attentive and Simple Graph Contrastive Learning for Recommendation
In contemporary society, individuals are inundated with a vast amount of redundant information, and recommendation systems have undoubtedly opened up new avenues for managing irrelevant data. Graph convolutional networks (GCNs) have demonstrated remarkable performance in the field of recommendation...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-03-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/5/2762 |