Abstract
In this paper, we propose a novel microaggregation algorithm to produce useful data in privacy preserving data publishing. Microaggregation is a clustering problem with known minimum and maximum group size constraints. We propose a local search algorithm that iteratively satisfies necessary constraints of an optimal solution of the problem. The algorithm solves the problem in O(n2) operations. Experimental results on real and synthetic data sets with different distributions confirm the effectiveness of the method.
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