Abstract
In this chapter, we present a taxonomy of frequent itemset and association rule hiding algorithms after having reviewed a large collection of independent works in this research area. The chapter is organized as follows. Section 3.1 presents a set of four orthogonal dimensions that we used to classify the existing methodologies by taking into consideration a number of parameters related to their workings. Following that, Section 3.2 straightens out the three principal classes of association rule hiding methodologies that have been proposed over the years and discusses the main properties of each class of approaches.
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© 2010 Springer Science+Business Media, LLC
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Gkoulalas-Divanis, A., Verykios, V.S. (2010). Classes of Association Rule Hiding Methodologies. In: Association Rule Hiding for Data Mining. Advances in Database Systems, vol 41. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6569-1_3
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DOI: https://doi.org/10.1007/978-1-4419-6569-1_3
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Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-6568-4
Online ISBN: 978-1-4419-6569-1
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