An Unsupervised Text Mining Method for Relation Extraction from Biomedical Literature

The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation ext...

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Detalles Bibliográficos
Autores principales: Quan, Changqin, Wang, Meng, Ren, Fuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103846/
https://www.ncbi.nlm.nih.gov/pubmed/25036529
http://dx.doi.org/10.1371/journal.pone.0102039

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103846/
https://www.ncbi.nlm.nih.gov/pubmed/25036529
http://dx.doi.org/10.1371/journal.pone.0102039

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