• DocumentCode
    2860919
  • Title

    Knowledge Representation and Inductive Learning with XML

  • Author

    Wu, Xiaobing

  • Author_Institution
    The Australian National University, Canberra, Australia
  • fYear
    2004
  • fDate
    20-24 Sept. 2004
  • Firstpage
    491
  • Lastpage
    494
  • Abstract
    This paper presents a novel knowledge representation method and learning system for XML documents. The traditional machine learning methods which use attribute-value languages are not suitable for representing XML documents due to their complex structures. In this paper, we propose a decision-tree algorithm for XML learning, which is based on a rich representation language for structured data and driven by precision/recall heuristic.
  • Keywords
    HTML; Information management; Internet; Knowledge engineering; Knowledge representation; Learning systems; Logic; Machine learning algorithms; Markup languages; XML;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, 2004. WI 2004. Proceedings. IEEE/WIC/ACM International Conference on
  • Print_ISBN
    0-7695-2100-2
  • Type

    conf

  • DOI
    10.1109/WI.2004.10125
  • Filename
    1410851
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2860919