Multi-Source Entity Resolution for Genealogical Data



Efremova, Julia, Ranjbar-Sahraei, Bijan, Rahmani, Hossein, Oliehoek, Frans A ORCID: 0000-0003-4372-5055, Calders, Toon, Tuyls, Karl and Weiss, Gerhard
(2015) Multi-Source Entity Resolution for Genealogical Data. In: Population Reconstruction. Springer International Publishing, pp. 129-154. ISBN 9783319198835

[img] Text
Efremova15bookchap.pdf - Unspecified
Access to this file is embargoed until Unspecified.

Download (1MB)

Abstract

In this chapter, we study the application of existing entity resolution (ER) techniques on a real-world multi-source genealogical dataset. Our goal is to identify all persons involved in various notary acts and link them to their birth, marriage, and death certificates. We analyze the influence of additional ER features, such as name popularity, geographical distance, and co-reference information on the overall ER performance. We study two prediction models: Regression trees and logistic regression. In order to evaluate the performance of the applied algorithms and to obtain a training set for learning the models we developed an interactive interface for getting feedback from human experts. We perform an empirical evaluation on the manually annotated dataset in terms of precision, recall, and F-score. We show that using name popularity, geographical distance together with co-reference information helps to significantly improve ER results.

Item Type: Book Section
Subjects: ?? QA75 ??
Depositing User: Symplectic Admin
Date Deposited: 20 Oct 2015 07:41
Last Modified: 17 Dec 2022 01:33
DOI: 10.1007/978-3-319-19884-2_7
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/2032562