• DocumentCode
    1898941
  • Title

    Risk Rules Mining of Information System Based on Variable Precision Rough Set

  • Author

    Cheng, Xiaorong ; Geng, Xin ; Zhao, Huilan ; Zhang, Mingquan

  • Author_Institution
    Sch. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding, China
  • Volume
    2
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    622
  • Lastpage
    625
  • Abstract
    For evaluation of the risk in information system, variable precision rough set (VPRS) theory is emerging as a powerful tool for reasoning about data. The method for risk rules mining in information system based on VPRS is designed on the basis of related concepts of VPRS. Through the example of the assessment, it is considered that the method can not only reduce greatly the data, but also increase the validity of risk regulations.
  • Keywords
    data mining; data reduction; fuzzy reasoning; fuzzy set theory; information systems; risk analysis; rough set theory; VPRS theory; data reduction; fuzzy data reasoning; information system; risk rule mining; variable precision rough set theory; Automation; Computer networks; Computer science; Data processing; Information systems; Information technology; Internet; Risk analysis; Safety; Set theory; VPRS; information systems; risk rules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.385
  • Filename
    5287759