• DocumentCode
    523673
  • Title

    A New Method for Eliminating Redundant Association Rules

  • Author

    Xin, Ye ; Na, Wang ; Chunyu, Wang

  • Author_Institution
    Inst. of Inf. & Decision Technol., Dalian Univ. of Technol., Dalian, China
  • Volume
    1
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    32
  • Lastpage
    36
  • Abstract
    As one of the fundamental data mining methods, the association rule mining has widely been used in many fields. However, the existence of massive redundant rules has made the analysis very difficult, and has been a main barrier to efficient utilization of discovered association rules. This paper studies the characteristic of commonsense knowledge which is use to eliminate redundant association rules, and analyzes the impact of commonsense knowledge and the special rules whose confidence is 100% on the generation of redundant rules. Some theorems and corollaries of redundant rules are proposed and a new method for eliminating redundant rules based on these theories is proposed. This new method can prune some redundant rules by using commonsense knowledge and the special rules without calculating confidence, so it improved the efficiency of mining and the utilization of discovered association rules.
  • Keywords
    Association rules; Automation; Character generation; Customer relationship management; Data analysis; Data mining; Intrusion detection; Itemsets; Road accidents; Security; Association Rule Mining; Commonsense Knowledge; Redundant Rules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha, China
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.129
  • Filename
    5522795