• DocumentCode
    2161699
  • Title

    The sensitive feature selection for both English and Chinese text chunking

  • Author

    Ying-Hong, Liang ; Jin-xiang, Li ; De-fu, Zhou ; De-peng, Wang

  • Author_Institution
    JiangSu Province Support Software Eng. R&D, Center for Modern Inf. Technol. Applic. in Enterprise, Suzhou, China
  • Volume
    4
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    305
  • Lastpage
    309
  • Abstract
    Traditional text chunking approach is to identify many phrases using only one model, and the same features are used to identify these phrases too. So the helpful features of each phrase are ignored. In fact, different phrases have different helpful features. In this paper, the concept of ¿sensitive feature¿ is proposed, and the sensitive features of eleven English types and seven Chinese types of phrases are selected by dynamic comparison strategy. Through testing on the Multi-agent chunking model, the selected English and Chinese sensitive features are both effective.
  • Keywords
    multi-agent systems; natural language processing; text analysis; Chinese text; English text; multi-agent chunking model; phrase identification; sensitive feature selection; text chunking approach; Application software; Electronic mail; Hidden Markov models; Information technology; Learning systems; Natural language processing; Research and development; Software engineering; Statistical analysis; Testing; feature selection; model; text chunking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5585-0
  • Electronic_ISBN
    978-1-4244-5586-7
  • Type

    conf

  • DOI
    10.1109/ICCAE.2010.5451684
  • Filename
    5451684