• DocumentCode
    2499021
  • Title

    Data mining in a large database environment

  • Author

    Sung, S.Y. ; Wang, K. ; Chua, B.L.

  • Author_Institution
    Dept. of Inf. Syst. & Comput. Sci., Nat. Univ. of Singapore, Singapore
  • Volume
    2
  • fYear
    1996
  • fDate
    14-17 Oct 1996
  • Firstpage
    988
  • Abstract
    Data mining, the process of discovering hidden and potentially useful information from very large databases, has been recognized as one of the most promising research topics in the 1990s. The essential problem faced in the mining of association rules is the generation of large items, which are items that are present in at least s% (minimal support) of the total database tuples. As the large items and their counts information usually require much storage space, the minimal cover concept is introduced to achieve reductions in the storage size. Percentage contour, an extension of minimal cover, is further introduced to aid in the handling of large databases
  • Keywords
    deductive databases; knowledge acquisition; very large databases; association rules; data mining; database tuples; minimal cover; percentage contour; very large databases; Association rules; Computer science; Dairy products; Data analysis; Data mining; Electronic mail; Information systems; Machine learning; Marketing and sales; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1996., IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-3280-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.1996.571213
  • Filename
    571213