• DocumentCode
    2486068
  • Title

    Word Segmentation Using Domain Knowledge Based on Conditional Random Fields

  • Author

    Fukuda, Takuya ; Izumi, Masataka ; Miura, Takao

  • Author_Institution
    Hosei Univ., Tokyo
  • Volume
    2
  • fYear
    2007
  • fDate
    29-31 Oct. 2007
  • Firstpage
    436
  • Lastpage
    439
  • Abstract
    In this investigation, we propose an experimental approach for word segmentation in Japanese under domain-dependent situation. We apply Conditional Random Fields (CRF) to our issue. CRF learns several probabilistic parameters from training data with specific feature functions dependent on domains. Here we propose how to define domain specific feature functions.
  • Keywords
    learning (artificial intelligence); natural language processing; probability; random processes; text analysis; Japanese word segmentation; conditional random field; domain knowledge; domain specific feature function; probabilistic parameter; text processing; training data; Artificial intelligence; Dictionaries; Natural languages; Pattern analysis; Speech; Statistics; Stochastic processes; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2007. ICTAI 2007. 19th IEEE International Conference on
  • Conference_Location
    Patras
  • ISSN
    1082-3409
  • Print_ISBN
    978-0-7695-3015-4
  • Type

    conf

  • DOI
    10.1109/ICTAI.2007.93
  • Filename
    4410418