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Generalization is a popular technique to realize k-anonymity. However, when the distribution of original data is uneven, generalization will distort the data greatly, which makes the anonymous data low utility. To address the problem, we propose a GN method, which limits the degree of generalization by adding noise tuples during anonymization. We also(More)
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