Comparing Classifiers in Historical Census Linkage

Abstract

Linking multiple data collections to create longitudinal data is an important research problem with multiple applications. Longitudinal data allows analysts to perform studies that would be unfeasible otherwise. In our research we are interested in linking historical census collections to create longitudinal data that would allow tracking people overtime. The goal of the linking is to identify the same person in multiple census collections. A classification system is employed to make the decision if two people are the same or not, based on their characteristics. In this paper we present an empirical study where we explore the use of three different classifiers in a record linkage system and we evaluate their performance.