• DocumentCode
    538894
  • Title

    Research of Attribute Reduction Algorithm about Knowledge System

  • Author

    Lihua, Hu ; Shifei, Ding ; Hao, Ding ; Hu, Wang

  • Author_Institution
    Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
  • Volume
    2
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    103
  • Lastpage
    106
  • Abstract
    Rough set (RS) theory is a mathematical tool to deal with vagueness and uncertainty effectively developed in recent years. It has been applied widely in data mining, artificial intelligence, decision support system, pattern recognition, etc. In RS theory, Attribute Reduction (AR) is one of the most important and key contents. Many scholars all over the world have made a considerable amount of research about it. This paper summarizes AR algorithms based on knowledge system, and lays stress on basic principles, existing problems and disadvantages about AR algorithms. The future direction and trends of AR research are discussed in the end.
  • Keywords
    knowledge based systems; rough set theory; artificial intelligence; attribute reduction algorithm; data mining; decision support system; knowledge system; mathematical tool; pattern recognition; rough set theory; Algorithm design and analysis; Approximation algorithms; Approximation methods; Complexity theory; Data mining; Knowledge based systems; Lattices; attribute reduction (AR); discernibility matrix; knowledge system; positive region; rough set (RS);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.241
  • Filename
    5708797