• DocumentCode
    2338455
  • Title

    High precision English base noun phrase identification based on "waterfall" model

  • Author

    Liang, Ying-Hong ; Zhao, Tie-jun ; Yu, Hao ; Yao, Jian-Min

  • Author_Institution
    MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., China
  • Volume
    8
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    4902
  • Abstract
    Based on classical model that used by software exploitation in the subject of Software Engineering - waterfall model, a high precision model for English noun phrase identification is presented. In this model, three important features (interior structure, context information and boundary character) in base noun phrase identification are orderly used, and the relative method (the rule method, the transfer-based and error-driven method, and the boundary statistic method) are used from top to bottom. Thus the precision of base noun phrase identification improved steadily. The "waterfall" model combined the rule method and the statistical method so as to make them complement each other. The precision of base noun phrase identification achieves 98.10% and the F score is 95.25%. Compared to other method, our method achieves the highest precision and F score.
  • Keywords
    computational linguistics; natural languages; software engineering; Software Engineering waterfall model; boundary character; boundary statistic method; context information; error-driven method; high precision English base noun phrase identification; interior structure; probability metric; rule method; transfer-based method; Context modeling; Electronic mail; Forestry; Laboratories; Natural language processing; Probability; Software engineering; Speech processing; Statistical analysis; Text processing; Noun phrase; probability metric; transfer rule; waterfall model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527806
  • Filename
    1527806