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A Globally Optimal k-Anonymity Method for the De-Identification of Health Data
Journal of the American Medical Informatics Association, 10/06/09
Emam KE et al. – For the de–identification of health datasets, OLA is an improvement on existing k–anonymity algorithms in terms of information loss and performance.
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