• DocumentCode
    3025308
  • Title

    The Research of Chinese Automatic Word Segmentation In Hierarchical Model Dictionary Binary Tree

  • Author

    Xiangang, Luo ; Jin, Luo ; Zhong, Xie

  • Author_Institution
    Fac. of Inf. Eng., China Univ. of Geosci., Wuhan, China
  • fYear
    2009
  • fDate
    25-26 April 2009
  • Firstpage
    321
  • Lastpage
    324
  • Abstract
    With the continuous development and growing popularity of the Internet, the amount of information on-line is in the explosive growth. How to find out the information that we need correctly and quickly from the mass data, then put in the front. Under this background, the Internet search engine grows up rapidly. This article describes the search engine on the general principle and common technology, and on this basis, combined with analyzeing the existing technology of Chinese automatic word segmentation, then to achieve a "wide-based segmentation of the largest positive scan," the Chinese word segmentation algorithm. According to the full text index technology, information search engine uses the means both of by word index and words index.Then, through the set of high-speed computing, and retrieve the information of users\´ requriements. Finally, using hierarchical model lexicon binary tree, which reserched and realized the model of information search engine.
  • Keywords
    indexing; information retrieval; natural language processing; search engines; text analysis; trees (mathematics); Chinese automatic word segmentation; Internet; hierarchical model dictionary binary tree; information search engine; lexicon binary tree; word index; Binary trees; Data engineering; Databases; Dictionaries; Geology; Humans; IP networks; Information retrieval; Search engines; Web and internet services; Chinese Automatic Word Segmentation; hierarchical model; search engine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database Technology and Applications, 2009 First International Workshop on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3604-0
  • Type

    conf

  • DOI
    10.1109/DBTA.2009.27
  • Filename
    5207750