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Embedding Learning with Triple Trustiness on Noisy Knowledge Graph
Embedding learning on knowledge graphs (KGs) aims to encode all entities and relationships into a continuous vector space, which provides an effective and flexible method to implement downstream knowledge-driven artificial intelligence (AI) and natural language processing (NLP) tasks. Since KG const...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7514427/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e21111083 |
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