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Indexed by:期刊论文

Date of Publication:2018-07-01

Journal:IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS

Included Journals:SCIE、CPCI-S、Scopus

Volume:15

Issue:4

Page Number:1325-1332

ISSN No.:1545-5963

Key Words:Trigger detection; two-stage method; word embeddings; feature selection

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.