Cargando…
BioWordVec, improving biomedical word embeddings with subword information and MeSH
Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlabeled text, ignoring the information present in the...
Autores principales: | Zhang, Yijia, Chen, Qingyu, Yang, Zhihao, Lin, Hongfei, Lu, Zhiyong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510737/ https://www.ncbi.nlm.nih.gov/pubmed/31076572 http://dx.doi.org/10.1038/s41597-019-0055-0 |
Ejemplares similares
-
Similarity-Based Unsupervised Spelling Correction Using BioWordVec: Development and Usability Study of Bacterial Culture and Antimicrobial Susceptibility Reports
por: Kim, Taehyeong, et al.
Publicado: (2021) -
Automated MeSH Indexing of Biomedical Literature Using Contextualized Word Representations
por: Koutsomitropoulos, Dimitrios A., et al.
Publicado: (2020) -
Biomedical event trigger detection by dependency-based word embedding
por: Wang, Jian, et al.
Publicado: (2016) -
MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm
por: Guo, Zhen-Hao, et al.
Publicado: (2020) -
subs2vec: Word embeddings from subtitles in 55 languages
por: van Paridon, Jeroen, et al.
Publicado: (2020)