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Impact of variations in anonymous record linkage on weight distribution and classification.

作者信息

Nasseh Daniel, Stausberg Jürgen

机构信息

IBE, Ludwig-Maximilians-Universität München, Germany.

出版信息

Stud Health Technol Inform. 2013;192:922.

PMID:23920696
Abstract

Anonymous or privacy preserving record linkage is the term for systems allowing the linkage of data from different sources while maintaining an individual's anonymity. This work displays the impact of variations in the process of generating weights in a probabilistic record linkage system on different datasets, the resulting set of weights of candidate pairs and consequently on the final classification process. Furthermore, the results give insight into general problems of current unsupervised classification methods.

摘要

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