• DocumentCode
    721228
  • Title

    Implementation of coherent rule mining algorithm for association rule mining

  • Author

    Davale, Aditya A. ; Shende, Shailendra W.

  • Author_Institution
    Dept. of Inf. Technol., Yeshwantrao Chavan Coll. of Eng., Nagpur, India
  • fYear
    2015
  • fDate
    25-27 Feb. 2015
  • Firstpage
    538
  • Lastpage
    541
  • Abstract
    In the data mining field, association rules are generated from domain knowledge which is evaluated from the minimum support threshold value. The accuracy in setting up this threshold directly influences the number and the quality of association rules discovered. The number of association rules discovered is large in numbers but still misses some interesting rules and the rule´s quality. So, the solution to this is the use of propositional logic to generate the association rules to avoid loss of rules. Coherent rules are discovered from the propositional logic so it does not require the domain expert. The coherent rules are discovered without knowing the value of minimum threshold. So, there is no need of deciding the threshold value. The results are compared with results apriori algorithm.
  • Keywords
    data mining; formal logic; association rule mining; coherent rule mining algorithm; data mining; domain expert; minimum support threshold value; minimum threshold; propositional logic; Algorithm design and analysis; Animals; Association rules; Classification algorithms; Dairy products; Market research; association rules; data mining; support;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015 International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-8432-9
  • Type

    conf

  • DOI
    10.1109/ABLAZE.2015.7154920
  • Filename
    7154920