Thesaurus-based word embeddings for automated biomedical literature classification

The special nature, volume and broadness of biomedical literature pose barriers for automated classification methods. On the other hand, manually indexing is time-consuming, costly and error prone. We argue that current word embedding algorithms can be efficiently used to support the task of biomedi...

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Detalles Bibliográficos
Autores principales: Koutsomitropoulos, Dimitrios A., Andriopoulos, Andreas D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2021
Materias:
Special issue on Advances of Neural Computing phasing challenges in the era of 4th industrial revolution
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111057/
https://www.ncbi.nlm.nih.gov/pubmed/33994670
http://dx.doi.org/10.1007/s00521-021-06053-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111057/
https://www.ncbi.nlm.nih.gov/pubmed/33994670
http://dx.doi.org/10.1007/s00521-021-06053-z

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