• DocumentCode
    1727639
  • Title

    An efficient clustering algorithm for market basket data based on small large ratios

  • Author

    Yun, Ching-Huang ; Chuang, Kun-Ta ; Chen, Ming-Syan

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    505
  • Lastpage
    510
  • Abstract
    In this paper we devise an efficient algorithm for clustering market-basket data items. In view of the nature of clustering market basket data, we devise in this paper a novel measurement, called the small-large (abbreviated as SL) ratio, and utilize this ratio to perform the clustering. With this SL ratio measurement, we develop an efficient clustering algorithm for data items to minimize the SL ratio in each group. The proposed algorithm not only incurs an execution time that is significantly smaller than that by prior work but also leads to the clustering results of very good quality
  • Keywords
    data mining; pattern clustering; SL ratio measurement; clustering algorithm; clustering analysis; data mining; execution time; market basket data; small large ratios; Association rules; Clustering algorithms; Costs; Damping; Data analysis; Data mining; Marine vehicles; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Software and Applications Conference, 2001. COMPSAC 2001. 25th Annual International
  • Conference_Location
    Chicago, IL
  • ISSN
    0730-3157
  • Print_ISBN
    0-7695-1372-7
  • Type

    conf

  • DOI
    10.1109/CMPSAC.2001.960660
  • Filename
    960660