Representation Learning: Recommendation With Knowledge Graph via Triple-Autoencoder
The last decades have witnessed a vast amount of interest and research in feature representation learning from multiple disciplines, such as biology and bioinformatics. Among all the real-world application scenarios, feature extraction from knowledge graph (KG) for personalized recommendation has ac...
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| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Frontiers Media S.A.
2022-06-01
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| Seri Bilgileri: | Frontiers in Genetics |
| Konular: | |
| Online Erişim: | https://www.frontiersin.org/articles/10.3389/fgene.2022.891265/full |
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