• DocumentCode
    3424573
  • Title

    Hierachical fuzzy set-based deep Web source classification

  • Author

    Wang Hai-long ; Yue Liang ; Zhao Peng-Peng ; Cui Zhi-Ming

  • Author_Institution
    Inst. of Intell. Inf. Process. & Applic., Soochow Univ., Suzhou, China
  • Volume
    5
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Abstract
    This paper presents a classification method of data source using fuzzy set and probabilistic model. The words of each domain are classified into characteristic words and general words according to their contribution to the current domain. The fuzzy set is introduced into the simplification process of characteristic words and the common words as the normalized glossary tool, which can be able to find more precise glossary in the homepage text. And a vocabulary probabilistic model is build after the normalized process in various domains, these words are classified by calculating the distance between the data source form vector and each domain vector.
  • Keywords
    Internet; classification; fuzzy set theory; glossaries; probability; text analysis; vocabulary; characteristic word; common word; data source form vector; deep Web source classification; domain vector; general word; hierarchical fuzzy set; homepage text; normalized glossary tool; vocabulary probabilistic model; Application software; Classification tree analysis; Databases; Electronic mail; Fuzzy sets; Information processing; Internet; Sea surface; Terminology; Vocabulary; deep Web; hierarchical fuzzy set; source classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Design and Applications (ICCDA), 2010 International Conference on
  • Conference_Location
    Qinhuangdao
  • Print_ISBN
    978-1-4244-7164-5
  • Electronic_ISBN
    978-1-4244-7164-5
  • Type

    conf

  • DOI
    10.1109/ICCDA.2010.5541144
  • Filename
    5541144