MB-AGCL: multi-behavior adaptive graph contrast learning for recommendation
Abstract Graph Convolutional Networks (GCNs) have achieved remarkable success in recommendation systems by leveraging higher-order neighborhoods. In recent years, multi-behavior recommendation has addressed the challenges of data sparsity and cold start problems to some extent. However, the introduc...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-04-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-025-01880-2 |
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