A Two-Stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings.
IEEE/ACM Trans Comput Biol Bioinform
; 15(4): 1325-1332, 2018.
Article
en En
| MEDLINE
| ID: mdl-28622674
ABSTRACT
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which divides trigger detection into recognition stage and classification stage, and different features are selected in each stage. In the first stage, we select the features which are more suitable for recognition, and in the second stage, the features that are more helpful to classification are adopted. Furthermore, we integrate word embeddings to represent words semantically and syntactically. On the multi-level event extraction (MLEE) corpus test dataset, our method achieves an F-score of 79.75 percent, which outperforms the state-of-the-art systems.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Aplicaciones de la Informática Médica
/
Minería de Datos
/
Aprendizaje Automático
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Revista:
ACM Trans Comput Biol Bioinform
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2018
Tipo del documento:
Article