Febrl: a freely available record linkage system with a graphical user interface
HDKM '08 Proceedings of the second Australasian workshop on Health data and knowledge management - Volume 80
Accurate Synthetic Generation of Realistic Personal Information
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Geocode Matching and Privacy Preservation
Privacy, Security, and Trust in KDD
A taxonomy of privacy-preserving record linkage techniques
Information Systems
An efficient two-party protocol for approximate matching in private record linkage
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
An iterative two-party protocol for scalable privacy-preserving record linkage
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
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Data linkage is the task of matching and aggregating records that relate to the same entity from one or more data sets. A related technique is geocoding, the matching of ad- dresses to their geographic locations. As data linkage is often based on personal information (like names and ad- dresses), privacy and confidentiality are of paramount im- portance. In this paper we present an overview of current approaches to privacy-preserving data linkage, and dis- cuss their limitations. Using real-world scenarios we illus- trate the significance of developing improved techniques for automated, large scale and distributed privacy-preserving linking and geocoding. We then discuss four core research areas that need to be addressed in order to make linking and geocoding of large confidential data collections feasible.