Vol.35, No.5, 2020, pp.311-319, doi:
OPEN ACCESS
ARTICLE
Event Trigger Recognition Based on Positive and Negative Weight Computing and its Application
  • Tao Liao1,‡, Weicheng Fu1,†, Shunxiang Zhang1,*, Zongtian Liu2,§
1 School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China
2 School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China
* Corresponding Authors: Shunxiang Zhang, sxzhang@aust.edu.cn
† 1425548176@qq.com
‡ tliao@aust.edu.cn
§ ztliu@shu.edu.cn
Abstract
Event trigger recognition is a sub-task of event extraction, which is important for text classification, topic tracking and so on. In order to improve the effectiveness of using word features as a benchmark, a new event trigger recognition method based on positive and negative weight computing is proposed. Firstly, the associated word feature, the part-of-speech feature and the dependency feature are combined. Then, the combination of these three features with positive and negative weight computing is used to identify triggers. Finally, the text classification is carried out based on the event triggers. Findings from our experiments show that the application of our method achieves ideal results.
Keywords
Event trigger recognition, Associated word, Dependency, Part-of-speech, Positive and negative weight computing, Text classification
Cite This Article
T. Liao, W. Fu, S. Zhang and Z. Liu, "Event trigger recognition based on positive and negative weight computing and its application," Computer Systems Science and Engineering, vol. 35, no.5, pp. 311–319, 2020.
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