• DocumentCode
    2917412
  • Title

    An Incremental Updating Algorithm for Online Mining Association Rules

  • Author

    Yubo, Jia ; Yuntao, Duan ; Yongli, Wang

  • Author_Institution
    Inst. of Inf. & Electron, Zhejiang Sci-Tech Univ., Hangzhou, China
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    144
  • Lastpage
    148
  • Abstract
    Aimed at the limitation of the current FUP algorithm, which readily led to the low efficiency of frequent itemset of the updated database, a novel association rules mining algorithm named QAIS which is different from the classical dual phrase was proposed. On the basis of QAIS, an improved association rules mining algorithm named AIU was put forward further. AIU can efficiently maintain association rules when the transaction database was updated. At the same time, the minimum support and confidence were not changed. Experiments showed the proposed algorithm was appropriate to online association rules mining.
  • Keywords
    data analysis; data mining; QAIS algorithm; incremental updating algorithm; online association rule mining; transaction database; Algorithm design and analysis; Association rules; Computer science; Data mining; Electrons; Information systems; Itemsets; Iterative algorithms; Maintenance engineering; Transaction databases; association rules; data mining; incremental updating; online mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Mining, 2009. WISM 2009. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3817-4
  • Type

    conf

  • DOI
    10.1109/WISM.2009.37
  • Filename
    5369434