• DocumentCode
    1941325
  • Title

    FP-Growth Algorithm for Application in Research of Market Basket Analysis

  • Author

    Liu, Yongmei ; Guan, Yong

  • Author_Institution
    Capital Normal Univ., Beijing
  • fYear
    2008
  • fDate
    27-29 Nov. 2008
  • Firstpage
    269
  • Lastpage
    272
  • Abstract
    During the process of mining frequent item sets, when minimum support is little, the production of candidate sets is a kind of time-consuming and frequent operation in the mining algorithm. The FP growth algorithm does not need to produce the candidate sets, the database which provides the frequent item set is compressed to a frequent pattern tree (or FP tree), and frequent item set is mining by using of FP tree. For the sake of researching market basket analysis, the frequent-pattern is introduced, Visual C++ is applied to design the program to mine the frequent item sets. In view of the frequent K-item set, the various results are contrasted, the goods which is sell possibly at the same time in the supermarket is arranged in the same place.
  • Keywords
    business data processing; data mining; FP growth algorithm; Visual C++; frequent K-item set; market basket analysis; mining algorithm; Algorithm design and analysis; Association rules; Business; Costs; Data mining; Marketing and sales; Organizational aspects; Partitioning algorithms; Production; Visual databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Cybernetics, 2008. ICCC 2008. IEEE International Conference on
  • Conference_Location
    Stara Lesna
  • Print_ISBN
    978-1-4244-2874-8
  • Electronic_ISBN
    978-1-4244-2875-5
  • Type

    conf

  • DOI
    10.1109/ICCCYB.2008.4721419
  • Filename
    4721419