Release Time:2019-03-10  Hits:

Indexed by: Conference Paper

Date of Publication: 2016-01-01

Included Journals: CPCI-S

Page Number: 775-775

Key Words: Biomedical event extraction; Distributed representation; Deep learning; Convolutional neural network

Abstract: The two main problems of biomedical event extraction are trigger identification and argument detection which can both be considered as classification problems. In this paper, we propose a distributed representation method, which combines context, consisted by dependency-based word embedding, and task-based features represented in a distributed way on deep learning models to realize biomedical event extraction. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores compared to the state-of-the-art SVM method. This demonstrates that our proposed method is effective for biomedical event extraction.