• DocumentCode
    3146678
  • Title

    Pseudo-Association Rules algorithm in data mining

  • Author

    Jing, Furong ; Yang, Junhui ; Wen, XieFu

  • Author_Institution
    Sch. of Inf. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
  • Volume
    7
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    3070
  • Lastpage
    3074
  • Abstract
    In data mining we not only mine the potential association between items, but also estimate the existent association of items which is still reasonable whether or not. Association Rules is mainly used to find the useful knowledge of the items in the mass data. However with the time goes by or the environment changes, previous association rules between data items or initial rules might be not reasonable, so we should check these rules to find the unreasonable ones. An association rule can not find the unreasonable relation between the data items. In this paper, we regard the structure of rules found by association rules as a digraph, and propose the Pseudo-association Rules based on an association rule, which can find the unreasonable rules.
  • Keywords
    data mining; directed graphs; data item; data mining; digraph; knowledge; pseudoassociation rule; unreasonable rule; Association rules; Itemsets; Optimization; Presses; Web sites; Association Rules; Graph; Pseudo-association Rules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6495-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2010.5639748
  • Filename
    5639748