• DocumentCode
    1279156
  • Title

    Efficient mining of association rules in distributed databases

  • Author

    Cheung, David W. ; Ng, Vincent T. ; Fu, Ada W. ; Yongjian Fu

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Univ., Hong Kong
  • Volume
    8
  • Issue
    6
  • fYear
    1996
  • fDate
    12/1/1996 12:00:00 AM
  • Firstpage
    911
  • Lastpage
    922
  • Abstract
    Many sequential algorithms have been proposed for the mining of association rules. However, very little work has been done in mining association rules in distributed databases. A direct application of sequential algorithms to distributed databases is not effective, because it requires a large amount of communication overhead. In this study, an efficient algorithm called DMA (Distributed Mining of Association rules), is proposed. It generates a small number of candidate sets and requires only O(n) messages for support-count exchange for each candidate set, where n is the number of sites in a distributed database. The algorithm has been implemented on an experimental testbed, and its performance is studied. The results show that DMA has superior performance, when compared with the direct application of a popular sequential algorithm, in distributed databases
  • Keywords
    communication complexity; database theory; deductive databases; distributed algorithms; distributed databases; knowledge acquisition; DMA algorithm; association rules; candidate sets; communication overhead; distributed algorithm; distributed data mining; distributed databases; knowledge discovery; messages; partitioned database; performance; support-count exchange; Association rules; Computer science; Data mining; Distributed algorithms; Distributed databases; Economic forecasting; Partitioning algorithms; Testing; Transaction databases; Warehousing;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.553158
  • Filename
    553158