Cargando…
Supervised Learning and Knowledge-Based Approaches Applied to Biomedical Word Sense Disambiguation
Word sense disambiguation (WSD) is an important step in biomedical text mining, which is responsible for assigning an unequivocal concept to an ambiguous term, improving the accuracy of biomedical information extraction systems. In this work we followed supervised and knowledge-based disambiguation...
Autores principales: | Antunes, Rui, Matos, Sérgio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042812/ https://www.ncbi.nlm.nih.gov/pubmed/29236676 http://dx.doi.org/10.1515/jib-2017-0051 |
Ejemplares similares
-
Knowledge-based biomedical word sense disambiguation: comparison of approaches
por: Jimeno-Yepes, Antonio J, et al.
Publicado: (2010) -
A Learning-Based Approach for Biomedical Word Sense Disambiguation
por: Al-Mubaid, Hisham, et al.
Publicado: (2012) -
Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
por: Xu, Hua, et al.
Publicado: (2006) -
Collocation analysis for UMLS knowledge-based word sense disambiguation
por: Jimeno-Yepes, Antonio, et al.
Publicado: (2011) -
Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy
por: Alexopoulou, Dimitra, et al.
Publicado: (2009)