Interest-Aware Contrastive-Learning-Based GCN for Recommendation
Graph convolutional networks (GCNs) have shown great potential in recommender systems. GCN models contain multiple layers of graph convolutions to exploit signals from higher-order neighbors. In each graph convolution, the embedding of a user or item is influenced by its directly connected neighbors...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9968245/ |