Semi-supervised method for biomedical event extraction

BACKGROUND: Biomedical extraction based on supervised machine learning still faces the problem that a limited labeled dataset does not saturate the learning method. Many supervised learning algorithms for bio-event extraction have been affected by the data sparseness. METHODS: In this study, a semi-...

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Detalles Bibliográficos
Autores principales: Wang, Jian, Xu, Qian, Lin, Hongfei, Yang, Zhihao, Li, Yanpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909242/
https://www.ncbi.nlm.nih.gov/pubmed/24565105
http://dx.doi.org/10.1186/1477-5956-11-S1-S17

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909242/
https://www.ncbi.nlm.nih.gov/pubmed/24565105
http://dx.doi.org/10.1186/1477-5956-11-S1-S17

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