Diffusion Model as a Base for Cold Item Recommendation
Cold items are a critical problem in the recommendation domain because newly introduced items lack user–item interactions to train accurate collaborative filters (CFs). Recent studies have adopted neural networks such as MLPs and autoencoders to predict collaborative embeddings learned by CFs, using...
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| Asıl Yazarlar: | , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI AG
2025-04-01
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| Seri Bilgileri: | Applied Sciences |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/2076-3417/15/9/4784 |
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