Title :
Comparing Classifiers in Historical Census Linkage
Author :
Richards, Laura ; Antonie, Luiza ; Areibi, Shawki ; Grewal, Gary ; Inwood, Kris ; Ross, J. Andrew
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.
Keywords :
pattern classification; support vector machines; classification system; classifier; historical census collection; historical census linkage; longitudinal data; multiple census collection; multiple data collection; performance evaluation; record linkage system; support vector machine; Couplings; Databases; Educational institutions; Equations; Joining processes; Mathematical model; Support vector machines; classification; historical census; record linkage;
Conference_Titel :
Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4799-4275-6
DOI :
10.1109/ICDMW.2014.160