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Utility-driven assessment of anonymized data via clustering - Scientific Data

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Utility-driven assessment of anonymized data via clustering - Scientific Data

In this study, clustering is conceived as an auxiliary tool to identify groups of special interest. This approach was applied to a real dataset concerning an entire Portuguese cohort of higher education Law students. Several anonymized clustering scenarios were compared against the original cluster solution. The clustering techniques were explored as data utility models in the context of data anonymization, using k-anonymity and (ε, δ)-differential as privacy models.

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Utility-driven assessment of anonymized data via clustering - Scientific Data

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Utility-driven assessment of anonymized data via clustering - Scientific Data

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