• DocumentCode
    2096414
  • Title

    The Study on the Application of Data Mining Based on Association Rules

  • Author

    Fang, Luo ; Qizhi, Qiu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2012
  • fDate
    11-13 May 2012
  • Firstpage
    477
  • Lastpage
    480
  • Abstract
    Association rule mining finds interesting association or correlation relationships among a large set of data items, which is an important task of data mining. Meanwhile, Apriori is an influential algorithm for mining frequent itemsets for Boolean association rules. Firstly, the concept and the effect of association rules are introduced and the classic algorithms of association rule are analyzed. In Apriori algorithm, most time is consumed for scanning the database repeatedly. Therefore, the methods are presented about improving the Apriori algorithm efficiency, which reduces a lot of time of scanning database and shortens the computation time of the algorithm. Furthermore, several typical applications of association rules in Market-Basket Analysis are given.
  • Keywords
    Boolean functions; data mining; Apriori algorithm; Boolean association rules; data mining; frequent itemsets mining; market-basket analysis; Algorithm design and analysis; Association rules; Data warehouses; Itemsets; Wireless application protocol; Apriori algorithm; Association rule; Candidate itemset; Data mining; Frequent itemset;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Network Technologies (CSNT), 2012 International Conference on
  • Conference_Location
    Rajkot
  • Print_ISBN
    978-1-4673-1538-8
  • Type

    conf

  • DOI
    10.1109/CSNT.2012.108
  • Filename
    6200681