• DocumentCode
    3423803
  • Title

    Mining opened frequent itemsets to generate maximal Boolean association rules

  • Author

    Jiang, Baoqing ; Han, Chong ; Li, Lingsheng

  • Author_Institution
    Inst. of Data & Knowledge Eng., Henan Univ., Kaifeng, China
  • fYear
    2009
  • fDate
    17-19 Aug. 2009
  • Firstpage
    274
  • Lastpage
    277
  • Abstract
    Lots of association rules may be generated in the process of association rules minging. It leads to users hard to find important information they needed. The maximal Boolean association rules have the advantages that these rules contain a small number and don´t lose the rules´ information. Thereby it increased the efficiency of the users´ analysis about the rules and saved the storage space. Opened frequent itemsets and closed frequent itemsets can be used to mine the maximal Boolean association rules. In this paper, we analyse the property of maximal Boolean association rules and propose an algorithm of mining opened frequent itemset. Finally, we verify this algorithm by an example.
  • Keywords
    Boolean functions; data mining; closed frequent itemsets; maximal boolean association rules; opened frequent itemsets mining; Algorithm design and analysis; Association rules; Data mining; Diseases; Explosions; Itemsets; Knowledge engineering; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing, 2009, GRC '09. IEEE International Conference on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-1-4244-4830-2
  • Type

    conf

  • DOI
    10.1109/GRC.2009.5255112
  • Filename
    5255112