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k-anonymization is a basic technique for utilizing sensitive information in data mining without violating personal privacy, and can be efficiently achieved by a greedy k-member clustering, where each data record is coded reflecting cluster structures so that each anonymized record is indistinguishable from at least other k − 1 records. In this paper, with the goal of utilizing cooccurrence information,...
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