• DocumentCode
    2260813
  • Title

    Unknown place name detection base on YamCha for Japanese guidance QA system

  • Author

    Liu, Ye ; Ren, Fuji

  • Author_Institution
    Grad. Sch. of Adv. Technol. & Sci., Univ. of Tokushima, Tokushima, Japan
  • fYear
    2009
  • fDate
    24-27 Sept. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    We perform a research about Japanese sightseeing guidance question answering (QA) system. In this domain Web information retrieval approach is always being used. However for the Web information retrieval, Japanese unknown place word detection needs to be considered. Some famous places are known very well, such as "Kinkaku-ji", it can be recognized by morphological analysis. However, the recognition rate of Japanese complex place is so poor. Therefore, we proposed an approach of the Japanese unknown place word detection. We use YamCha, a tool based on support vector machines (SVMs). The goal is that we want to recognize the unknown sightseeing spots word from user\´s question. In the experiment of Japanese place word detection we have got excellent precision and recalling rates.
  • Keywords
    Internet; information retrieval; natural language processing; support vector machines; Japanese sightseeing guidance QA system; Japanese unknown place name detection; SVM; Web information retrieval approach; YamCha tool; morphological analysis; question answering system; support vector machine; unknown sightseeing spot word recognition rate; Data mining; Earth Observing System; Information retrieval; Natural languages; Silicon compounds; Support vector machine classification; Support vector machines; Training data; Japanese sightseeing place word detection; Support Vector Machine; YamCha;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-4538-7
  • Electronic_ISBN
    978-1-4244-4540-0
  • Type

    conf

  • DOI
    10.1109/NLPKE.2009.5313824
  • Filename
    5313824