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In this paper, we focus on the problem of preserving the data confidentiality when sharing the data for clustering. This problem poses new challenges for novel uses of privacy preserving data mining (PPDM) techniques. Specifically, this paper considers the synthetic data generation as a way to preserve the data privacy. One of the state of the art synthetic data generators is the IPSO family of methods. It has been stated that the use of IPSO to generate synthetic data is appropriate when thedoi:10.1109/fuzzy.2010.5584186 dblp:conf/fuzzIEEE/CanoLT10 fatcat:zqggliauurgeldhycu6ndmt7du