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Neural sentence embedding models for semantic similarity estimation in the biomedical domain
BACKGROUND: Neural network based embedding models are receiving significant attention in the field of natural language processing due to their capability to effectively capture semantic information representing words, sentences or even larger text elements in low-dimensional vector space. While curr...
Autores principales: | Blagec, Kathrin, Xu, Hong, Agibetov, Asan, Samwald, Matthias |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6460644/ https://www.ncbi.nlm.nih.gov/pubmed/30975071 http://dx.doi.org/10.1186/s12859-019-2789-2 |
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