• DocumentCode
    2335736
  • Title

    Application of data mining in supply chain management

  • Author

    An Chen ; Lu Liu ; Ning, Chen ; Guoping, Xia

  • Author_Institution
    Sch. of Manage., Beijing Univ. of Aeronaut. & Astronaut., China
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1943
  • Abstract
    Dealing with the very large database in supply chain management is a very important problem. Mining association rules and sequential patterns from large database has been recognized by many researchers in database systems and many other related management areas. In this paper, the research on data mining of supply chain is first introduced, then the four stages of the implementation of data mining are given. Many previous works focus on mining association rules in transaction database and sequential patterns at a single concept level, but there exists many phenomena of multiple level sequence patterns in practice. An effective multiple sequence patterns mining algorithm is presented in this paper. Finally, a case study is discussed
  • Keywords
    data mining; manufacturing data processing; stock control data processing; very large databases; association rule mining; data mining; knowledge discovery; multiple level sequence patterns; supply chain management; very large database; Association rules; Data mining; Database systems; Mathematics; Pattern recognition; Supply chain management; Supply chains; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
  • Conference_Location
    Hefei
  • Print_ISBN
    0-7803-5995-X
  • Type

    conf

  • DOI
    10.1109/WCICA.2000.862854
  • Filename
    862854