• Aris Gkoulalas-Divanis
  • Vassilios S. Verykios
Part of the Advances in Database Systems book series (ADBS, volume 41)


In this chapter we provide the background and terminology that are necessary for the understanding of association rule hiding. Specifically, in Section 2.1, we present the theory behind association rule mining and introduce the notion of the positive and the negative borders of the frequent itemsets. Following that, Section 2.2 explicitly states the goals of association rule hiding methodologies, discusses the different types of solutions that association rule hiding algorithms can produce, as well as it delivers the formal problem statement for association rule hiding and its popular variant, frequent itemset hiding.


Association Rule Frequent Pattern Frequent Itemsets Association Rule Mining Data Owner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Aris Gkoulalas-Divanis
    • 1
  • Vassilios S. Verykios
    • 2
  1. 1.Information Analytics LabIBM Research GmbH - ZurichRueschlikonSwitzerland
  2. 2.Department of Computer and Communication EngineeringUniversity of ThessalyVolosGreece

Personalised recommendations