• DocumentCode
    3037934
  • Title

    Research on Mining Association Rules in Distributed System

  • Author

    Wang, Ailing

  • Author_Institution
    Dept. of Math., Heze Univ., Heze, China
  • fYear
    2009
  • fDate
    24-26 July 2009
  • Firstpage
    472
  • Lastpage
    475
  • Abstract
    With the development of Intemet and the distributed database technology, a great deal of data is stored in the disrtibuted Web nodes and it is impossible to be stored in one single node on account of communication, efficiency and security. So it´s a very important research in the data mining domain. This paper makes a thorough research on mining association rules in the distributed database system. It extends the most classical algorithm Apriori based on distributed transactional database system. The system is realized based on the local global association rules mining solution. Finally the paper puts forward an efficient algorithm of getting association rules from frequent itemsets. This improved algorithm shows sound extension, short time complexity, small communication cost and simplicity.
  • Keywords
    data mining; distributed databases; learning (artificial intelligence); Apriori algorithm; data mining association rules; data mining domain research; distributed database system; Association rules; Business communication; Data engineering; Data mining; Deductive databases; Distributed databases; Electronic mail; Itemsets; Mathematics; Transaction databases; Keywords-association rules; data mining; distributed system; support;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-0-7695-3705-4
  • Type

    conf

  • DOI
    10.1109/BIFE.2009.113
  • Filename
    5208843