Combining Graph Contrastive Embedding and Multi-head Cross-Attention Transfer for Cross-Domain Recommendation
Abstract Cross-domain recommendation (CDR) has become an important research direction in the field of recommender systems due to the increasing demand for personalized recommendations across different domains. However, CDR faces multiple challenges, including data sparsity, popularity bias, and long...
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| Huvudupphov: | , , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Utgiven: |
SpringerOpen
2023-09-01
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| Serie: | Data Science and Engineering |
| Ämnen: | |
| Länkar: | https://doi.org/10.1007/s41019-023-00226-7 |
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