A multi-level graph attention network with contrastive learning outperforms prior methods on knowledge-aware recommendation by improving generalization across three comparison perspectives.
Self -Supervised Learning for Recommender Systems: A Survey[J]
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AusRec applies meta-learning to automatically weight multiple self-supervised tasks for improved social recommendation performance.
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Multi-Level Graph Attention Network Contrastive Learning for Knowledge-Aware Recommendation
A multi-level graph attention network with contrastive learning outperforms prior methods on knowledge-aware recommendation by improving generalization across three comparison perspectives.
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Automatic Self-supervised Learning for Social Recommendations
AusRec applies meta-learning to automatically weight multiple self-supervised tasks for improved social recommendation performance.