• DocumentCode
    3281473
  • Title

    Adaptive AFOPT algorithm

  • Author

    Györödi, Cornelia ; Györödi, Robert ; Pater, Mirela ; Boc, Ovidiu ; David, Zoltan

  • Author_Institution
    Dept. of Comput. Sci., Oradea Univ., Romania
  • fYear
    2005
  • fDate
    25-29 Sept. 2005
  • Abstract
    Mining frequent patterns is a fundamental part of data mining. Most of the previous studies adopt an a priori-like candidate set generation-and-test approach. The a priori is the first algorithm which uses the a priori property to prune the search space. In this paper the AFOPT algorithm is adapted for mining at different levels by using different support. Furthermore, the efficiency of this algorithm is being shown by comparing it to similar algorithms.
  • Keywords
    data mining; pattern classification; tree searching; a priori property; adaptive AFOPT algorithm; data mining; search space; Computer science; Costs; Data mining; Databases; Frequency; Informatics; Itemsets; Iterative algorithms; Test pattern generators; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numeric Algorithms for Scientific Computing, 2005. SYNASC 2005. Seventh International Symposium on
  • Print_ISBN
    0-7695-2453-2
  • Type

    conf

  • DOI
    10.1109/SYNASC.2005.17
  • Filename
    1595840