• DocumentCode
    496138
  • Title

    A Novel Extension Data Mining Approach Based on Rough Sets and Extension Sets

  • Author

    Zhi-hang, Tang ; Bao-an, Yang

  • Author_Institution
    Sch. of Comput. & Commun., Hunan Inst. of Eng., Xiangtan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    25-26 July 2009
  • Firstpage
    505
  • Lastpage
    509
  • Abstract
    The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. The main idea of rough set theory is to extract decision rules by attribute reduction and value reduction in the premises of keeping the ability of classification, reducing the condition attributes based on the extension set theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant rules based on the reduced attributes .To combine extension sets with rough sets pair analysis, a new synthetic evaluation approach is proposed. The result shows this method is quite valuable in knowledge discovery for large category complex information systems.
  • Keywords
    data mining; decision theory; pattern classification; rough set theory; attribute reduction; classification ability; data mining approach; decision rule extraction; extension set theory; knowledge discovery; large category complex information system; rough set method; synthetic evaluation approach; value reduction; Computer science; Data analysis; Data engineering; Data mining; Databases; Information systems; Information technology; Knowledge acquisition; Rough sets; Set theory; extension data mining; extension sets; rough sets; sets pair analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
  • Conference_Location
    Kiev
  • Print_ISBN
    978-0-7695-3688-0
  • Type

    conf

  • DOI
    10.1109/ITCS.2009.110
  • Filename
    5190122