2012/2013
r-Anonymized clustering
The 19th International Conference on Neural Information Processing (ICONIP 2012), Doha, Qatar
Author(s) | Wenye Li |
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Summary | Motivated by the practical needs in privacy-preserving data publishing, we study the problem of r-anonymized clustering. The problem is to minimize the total cost between objects and cluster-centers subject to a constraint that each cluster contains a minimum number of objects. To address the inherent computational difficulty, we exploit linear program relaxation with a specialized iterative rounding strategy to find high quality solutions in an efficient manner. We conduct a series of experiments to evaluate the performance of the methods, and demonstrate its application in privacy preserving disease mapping. |