An Empirical Comparison of Approaches to Approximate String Matching in Private Record Linkage

Due to the frequency of spelling and typographical errors in practical applications, record linkage algorithms have to use string similarity functions. In many legal contexts, identifiers such as names have to be encrypted before a record linkage can be attempted. Therefore, algorithms for computing string similarity functions with encrypted identifiers are essential for approximating string matching in private record linkage. This study reports an empirical evaluation of three promising approaches to compute similarities between identifiers in a privacy preserving manner.