• DocumentCode
    3195956
  • Title

    Association rules mining algorithm based on Rough Set

  • Author

    Xun Jiao ; Xu Lian-cheng ; Qi Lin

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
  • Volume
    1
  • fYear
    2012
  • fDate
    3-5 Aug. 2012
  • Firstpage
    361
  • Lastpage
    364
  • Abstract
    Association rules mining algorithm based on Rough Set theory is put forward using the idea of Rough Set theory, which applies the improved Apriori algorithm in association rules mining on the basis of Decision Table. The advantage of this method lies in three aspects, including the elimination of redundancy attributes, reducing the number of attributes, while scanning Decision Table just once can produce decision attribute sets. Application example analysis shows that this is an effective and fast data mining method.
  • Keywords
    data mining; decision tables; rough set theory; application example analysis; apriori algorithm; association rules mining algorithm; decision attribute sets; decision table; rough set theory; Computers; Association rules mining; Decision Table; Rough Set; redundancy attributes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology in Medicine and Education (ITME), 2012 International Symposium on
  • Conference_Location
    Hokodate, Hokkaido
  • Print_ISBN
    978-1-4673-2109-9
  • Type

    conf

  • DOI
    10.1109/ITiME.2012.6291318
  • Filename
    6291318