2010
DOI: 10.1016/j.eswa.2009.09.054
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Density-based microaggregation for statistical disclosure control

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Cited by 57 publications
(55 citation statements)
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“…Any remaining records are then added to their respective nearest clusters. Experimental results indicate that MDAV-1 incurs slightly less information loss than MDAV [29]. Another variant of the MDAV method, called MDAV-generic, is proposed by Domingo-Ferrer and Torra [8], where by the threshold 2k is altered to 3k.…”
Section: Previous Microaggregation Methodsmentioning
confidence: 99%
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“…Any remaining records are then added to their respective nearest clusters. Experimental results indicate that MDAV-1 incurs slightly less information loss than MDAV [29]. Another variant of the MDAV method, called MDAV-generic, is proposed by Domingo-Ferrer and Torra [8], where by the threshold 2k is altered to 3k.…”
Section: Previous Microaggregation Methodsmentioning
confidence: 99%
“…For fixed-size microaggregation, the partition is done by dividing a dataset into clusters that have size k, except perhaps one cluster which has a size between k and (2k − 1), depending on the total number of records n and the anonymity parameter k. For the data-oriented microaggregation, the partition is done by allowing all clusters with sizes between k and (2k − 1). Intuitively, fixed-size methods reduce the search space, and thus are more computationally efficient than data-oriented methods [29]. However, data-oriented methods can adapt to different values of k and various data distributions and thus may achieve lower information loss than fixed-size methods.…”
Section: Previous Microaggregation Methodsmentioning
confidence: 99%
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