UPRec: User-aware Pre-training for sequential Recommendation
Recent years witness the success of pre-trained models to alleviate the data sparsity problem in recommender systems. However, existing pre-trained models for recommendation mainly focus on leveraging universal sequence patterns from user behavior sequences and item information, whereas ignore heter...
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| Autori principali: | , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
KeAi Communications Co. Ltd.
2023-01-01
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| Serie: | AI Open |
| Soggetti: | |
| Accesso online: | http://www.sciencedirect.com/science/article/pii/S2666651023000104 |
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