• DocumentCode
    2876785
  • Title

    Applications of assoiation rules hiding heuristic approaches

  • Author

    Farea, Afrah ; Karci, Ali

  • Author_Institution
    Comput. Eng. Dept., Inonu Univ., Malatya, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    2650
  • Lastpage
    2653
  • Abstract
    Data Mining allows large database owners to extract useful knowledge that could not be deduced with traditional approaches like statistics. However, these sometimes reveal sensitive knowledge or preach individual privacies. The term sanitization is given to the process of changing original database into another one from which we can mine without exposing sensitive knowledge. In this paper, we give a detailed explanation of some heuristic approaches for this purpose. We applied them on a number of publically available datasets and examine the results.
  • Keywords
    data mining; data privacy; association rules hiding heuristic; data mining; database sanitization; Data mining; Itemsets; Data Mining; association rule; confidence; frequent pattern; itemset; sanitization; support; transaction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7130434
  • Filename
    7130434