• DocumentCode
    147630
  • Title

    Mining probabilistic association rules from uncertain databases with pruning

  • Author

    Peterson, Erich A. ; Liang Zhang ; Peiyi Tang

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Arkansas at Little Rock, Little Rock, AR, USA
  • fYear
    2014
  • fDate
    13-16 March 2014
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    In this paper, we rigorously define the problem of mining probabilistic association rules from uncertain databases. We further analyze the probability distribution space of a candidate probabilistic association rule, and propose an efficient mining algorithm with pruning to find all probabilistic association rules from uncertain databases.
  • Keywords
    data mining; statistical distributions; candidate probabilistic association rule; mining algorithm; probabilistic association rules mining; probability distribution space; pruning; uncertain databases; Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SOUTHEASTCON 2014, IEEE
  • Conference_Location
    Lexington, KY
  • Type

    conf

  • DOI
    10.1109/SECON.2014.6950736
  • Filename
    6950736
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=147630