DocumentCode :
2112525
Title :
Chinese Semantic Role Labeling Based on Genetic Algorithm
Author :
Mao Ning ; Shao Yanqiu ; Liang Chunxia
Author_Institution :
Res. Dept., Beijing City Univ., Beijing, China
Volume :
3
fYear :
2012
fDate :
4-7 Dec. 2012
Firstpage :
127
Lastpage :
131
Abstract :
To find the effective features from many syntactic features could improve the efficiency and accuracy of the semantic role labeling system. Based on the original semantic role labeling system, the genetic algorithm is used to optimize those syntactic features. From the experiment results, it could be concluded that the syntactic feature selection based on genetic algorithm is efficient. The system uses fewer features, but achieves almost the same F value as the whole extended model.
Keywords :
genetic algorithms; natural language processing; word processing; Chinese semantic role labeling system; F value; genetic algorithm; syntactic feature selection; genetic algorithm; semantic analysis; semantic role labeling; syntactic structure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-6057-9
Type :
conf
DOI :
10.1109/WI-IAT.2012.173
Filename :
6511663
Link To Document :
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