Multi-behavior aware recommendation with joint contrastive learning and reinforced negative sampling
Abstract Traditional recommendation systems usually rely on single user-item interaction information to capture the characteristics of users and items. However, in real-world applications, the interactions between users and items are far more diverse. Therefore, efficiently integrating multidimensio...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-025-01970-1 |
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