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...
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| Автори: | , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Nature Portfolio
2025-10-01
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| Серія: | Scientific Reports |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1038/s41598-025-15890-0 |
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