Table of Content

Open Access iconOpen Access

ARTICLE

crossmark

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, email
email
email
§ email

Computer Systems Science and Engineering 2020, 35(5), 311-319. https://doi.org/10.32604/csse.2020.35.311

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


Cite This Article

APA Style
Liao, T., Fu, W., Zhang, S., Liu, Z. (2020). Event trigger recognition based on positive and negative weight computing and its application. Computer Systems Science and Engineering, 35(5), 311-319. https://doi.org/10.32604/csse.2020.35.311
Vancouver Style
Liao T, Fu W, Zhang S, Liu Z. Event trigger recognition based on positive and negative weight computing and its application. Comput Syst Sci Eng. 2020;35(5):311-319 https://doi.org/10.32604/csse.2020.35.311
IEEE Style
T. Liao, W. Fu, S. Zhang, and Z. Liu "Event Trigger Recognition Based on Positive and Negative Weight Computing and its Application," Comput. Syst. Sci. Eng., vol. 35, no. 5, pp. 311-319. 2020. https://doi.org/10.32604/csse.2020.35.311



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2038

    View

  • 1266

    Download

  • 0

    Like

Share Link