• DocumentCode
    3285327
  • Title

    Accessing Deep Web Using Automatic Query Translation Technique

  • Author

    Liang, Hao ; Zuo, Wanli ; Ren, Fei ; Sun, Chong

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun
  • Volume
    2
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    267
  • Lastpage
    271
  • Abstract
    The information on the surface Web is supported by the deep Web, which can not be accessed directly by the search engines or the Web crawlers. The only way to access the backend database is through query interface. Automatic extracting query attributes from the query form and automatic translating source queries into target queries is a solvable way for addressing the current limitations in accessing deep Web data sources. We use the WordNet as a kind of ontology technique to enrich the attributes contained in the semantic form. Because of Web semantic constraint provided by the query form, some attributes are co-occurred and the others are exclusive sometimes. To generate a valid query, we have to reconcile the key attributes and their semantic relations. We show a method to find the semantic relation of the attributes in the sources query from and different forms and translate query between different query forms.
  • Keywords
    ontologies (artificial intelligence); query processing; semantic Web; Web crawlers; Web semantic; WordNet; automatic query translation technique; deep Web; ontology; search engines; source queries; target queries; Computer science; Crawlers; Data mining; Databases; Educational institutions; Educational technology; Fuzzy systems; Information science; Ontologies; Search engines; Deep Web; Surface Web; WordNet; ontology.;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
  • Conference_Location
    Shandong
  • Print_ISBN
    978-0-7695-3305-6
  • Type

    conf

  • DOI
    10.1109/FSKD.2008.18
  • Filename
    4666120