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Improving record linkage with supervised learning for disclosure risk assessment
2012
Information Fusion
In data privacy, record linkage can be used as an estimator of the disclosure risk of protected data. To model the worst case scenario one normally attempts to link records from the original data to the protected data. In this paper we introduce a parametrization of record linkage in terms of a weighted mean and its weights, and provide a supervised learning method to determine the optimum weights for the linkage process. That is, the parameters yielding a maximal record linkage between the
doi:10.1016/j.inffus.2011.05.001
fatcat:jcdqgext6jbjnh3varrwkmmamm