Reduction Relaxation in Privacy Preserving Association Rules Mining

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 186)

Abstract

In Privacy Preserving Association Rules Mining, when frequent sets are discovered, the relaxation can be used to decrease the false negative error component and, in consequence, to decrease the number of true frequent itemsets that are missed. We introduce the new type of relaxation - the reduction relaxation that enable a miner to decrease and control the false negative error for different lengths of frequent itemsets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

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