• DocumentCode
    3461010
  • Title

    English Location Entity Recognition Based on Conditional Random Fields

  • Author

    Xiaolong Guo ; Yuncheng Du ; Xueqiang Lv ; Shuicai Shi

  • Author_Institution
    Chinese Inf. Process. Res. Center, Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • fYear
    2009
  • fDate
    7-9 Dec. 2009
  • Firstpage
    274
  • Lastpage
    277
  • Abstract
    Location entity detection is one task of automatic content extraction 2008 (ACE2008), which defines five types of entities. In this paper, the conditional random fields model is used to recognize the English location by selecting different characteristics. We select the features of English location dictionary, preposition prefix to improve the experimental results. Through calculating the recall, precision and F-value, we found that they are great impact of the quality by the characteristics. The experimental results show that, to a certain extent, more characteristics are selected, better result will be got.
  • Keywords
    dictionaries; information filtering; natural language processing; pattern recognition; statistical analysis; English location dictionary; English location entity recognition; conditional random fields; location entity detection; Automatic control; Character recognition; Data mining; Dictionaries; Information processing; Information science; Information technology; Meetings; NIST; Natural language processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4244-5543-0
  • Type

    conf

  • DOI
    10.1109/ICICIC.2009.193
  • Filename
    5412595