• DocumentCode
    1819924
  • Title

    An efficient algorithm for incremental mining of association rules

  • Author

    Chang, Chin-Chen ; Li, Yu-Chiang ; Lee, Jung-San

  • Author_Institution
    Dept. of Inf. Eng. & Comput. Sci., Feng Chia Univ., Taichung, Taiwan
  • fYear
    2005
  • fDate
    3-4 April 2005
  • Firstpage
    3
  • Lastpage
    10
  • Abstract
    Incremental algorithms can manipulate the results of earlier mining to derive the final mining output in various businesses. This study proposes a new algorithm, called the New Fast UPdate algorithm (NFUP) for efficiently incrementally mining association rules from a large transaction database. NFUP is a backward method that only requires scanning incremental database. Rather than rescanning the original database for some new generated frequent itemsets in the incremental database, we accumulate the occurrence counts of newly generated frequent itemsets and delete infrequent itemsets obviously. Thus, NFUP need not rescan the original database and to discover newly generated frequent itemsets. NFUP has good scalability in our simulation.
  • Keywords
    data mining; transaction processing; very large databases; New Fast UPdate algorithm; association rules; frequent itemsets; incremental database; incremental mining; large transaction database; Algorithm design and analysis; Association rules; Computer science; Data mining; Data warehouses; Information retrieval; Information science; Itemsets; Scalability; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research Issues in Data Engineering: Stream Data Mining and Applications, 2005. RIDE-SDMA 2005. 15th International Workshop on
  • ISSN
    1097-8585
  • Print_ISBN
    0-7695-2390-0
  • Type

    conf

  • DOI
    10.1109/RIDE.2005.6
  • Filename
    1498225