Exploiting Transfer Learning With Attention for In-Domain Top-N Recommendation
Cross-domain recommendation has recently been extensively studied, aiming to alleviate the data sparsity problem. However, user-item interaction data in the source domain is often not available, while user-item interaction data of various types in the same domain is relatively easy to obtain. This p...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8922693/ |