• 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