• DocumentCode
    3229523
  • Title

    A Semantic Learning Approach for Mapping Unstructured Query to Web Resources

  • Author

    Hoon, Gan Keng ; Keong, Phang Keat ; Kong, Tang Enya

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Technol., Malaya Univ., Kuala Lumpur
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    494
  • Lastpage
    497
  • Abstract
    The search that involves structured Web resources like XML data, services is still lagging of its own method and relying on contemporary search systems. This paper presents a method that learns semantics from structured information of these resources. Instead of committing the semantic meaning of resources to strict and formal vocabularies like ontology or data dictionary, we are interested to interpret the meaning based on the natural context of the resources. The semantics are used in search process, i.e. query reasoning and resource selection, to provide better answer in terms of context relevancy and clearer result description
  • Keywords
    learning (artificial intelligence); meta data; ontologies (artificial intelligence); query formulation; semantic Web; Web resource; XML data; data dictionary; formal vocabulary; mapping unstructured query; resource selection; semantic learning approach; Computer science; Data mining; Dictionaries; Gallium nitride; Information technology; Natural languages; Ontologies; Resource description framework; Vocabulary; XML;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2747-7
  • Type

    conf

  • DOI
    10.1109/WI.2006.24
  • Filename
    4061418