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...

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Detalles Bibliográficos
Autores principales: Blagec, Kathrin, Xu, Hong, Agibetov, Asan, Samwald, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
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

Internet

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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