• DocumentCode
    2757611
  • Title

    Assessment for Ontology-Supported Deep Web Search

  • Author

    An, Yoo Jung ; Chun, Soon Ae ; Huang, Kuo-chuan ; Geller, James

  • Author_Institution
    New Jersey Inst. of Technol., Newark, NJ
  • fYear
    2008
  • fDate
    21-24 July 2008
  • Firstpage
    382
  • Lastpage
    388
  • Abstract
    Ontologies could play an important role in assisting users in their search for Web pages. This paper considers the problem of constructing domain ontologies that support users in their Web search efforts and that increase the number of relevant Web pages that are returned. To achieve this goal, this paper suggests combining Deep Web information, which consists of dynamically generated Web pages, which cannot be indexed by the existing automated Web crawlers, with ontologies. Improvements when finding deep Web sites returned by a search engine are assessed based on the framework formulated in this paper. Experimental results suggest that the proposed methods assist users in finding more relevant Web sites.
  • Keywords
    Web sites; ontologies (artificial intelligence); search engines; Web information; Web pages; Web search efforts; deep Web sites; ontology-supported deep Web search; Automobiles; Crawlers; Databases; Humans; Indexing; Ontologies; Search engines; Web pages; Web search; Web services; deep web; domain ontology; semantic deep web; web search engine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, 2008 10th IEEE Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-0-7695-3340-7
  • Type

    conf

  • DOI
    10.1109/CECandEEE.2008.117
  • Filename
    4785094