• DocumentCode
    2546834
  • Title

    A dynamic improved apriori algorithm and its experiments in web log mining

  • Author

    Luan, RuPeng ; Sun, SuFen ; Zhang, JunFeng ; Yu, Feng ; Zhang, Qian

  • Author_Institution
    Inst. of Agric. Scientech Inf., Beijing Acad. of Agric. & Forestry Sci., Beijing, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1261
  • Lastpage
    1264
  • Abstract
    Apriori algorithm is an influential data mining algorithm which can mining the frequent sets of Boolean association rules. But its efficiency is not high and cannot do dynamic mining, for these reasons a new association rules algorithm which is suitable for dynamic database mining was proposed. Furthermore, the new algorithm is applied to the web log mining. Compared with original algorithm, experiments show that the performance of the new algorithm is improved to some extent.
  • Keywords
    Web sites; data mining; Boolean association rule; Web log mining; data mining algorithm; dynamic database mining; dynamic improved apriori algorithm; Algorithm design and analysis; Association rules; Heuristic algorithms; Itemsets; Software algorithms; Apriori algorithm; correlation analysis; web log mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6234032
  • Filename
    6234032