• DocumentCode
    3232065
  • Title

    Algorithms of association rules extraction: State of the art

  • Author

    Hamida, Amdouni ; Mohsen, Gammoudi Mohamed

  • Author_Institution
    RIADI Lab., FST, Tunisia
  • fYear
    2011
  • fDate
    27-29 May 2011
  • Firstpage
    333
  • Lastpage
    339
  • Abstract
    More than a decade, the task of generating associative rules has received considerable attention by researchers because the great need of enterprise deciders to be assisted by systems taking into account unknown knowledge extracted from a huge volume of data. In this paper, we present a survey of the most known algorithms used for associative rules extraction. We give a comparative study between them and we show that they could be classified into some categories.
  • Keywords
    data mining; association rules extraction algorithms; data mining; enterprise deciders; knowledge extraction; Context; Associatives rules; Closed Itemsets; FCA; Frequent Itemsets; Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-61284-485-5
  • Type

    conf

  • DOI
    10.1109/ICCSN.2011.6014282
  • Filename
    6014282
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3232065