TítuloHeuristic Supervised Approach for Record Linkage
Publication TypeConference Paper
Year of Publication2012
AuthorsMurillo J, Abril D, Torra V
EditorTorra V, Narukawa Y, López B, Villaret M
Conference NameModeling Decisions for Artificial Intelligence (MDAI)
Volume7647
EditorialSpringer Berlin / Heidelber
Conference LocationGirona, Catalonia
Paginación210-221
Date Published21/11/2012
ISBN Number978-3-642-34619-4
Resumen

Record linkage is a well known technique used to link records from one database to records from another database which make reference to the same individuals. Although it is usually used in database integration, it is also used in the data privacy field for the disclosure risk evaluation of protected datasets. In this paper we compare two different supervised algorithms which rely on distance-based record linkage techniques, specifically using the Choquet integral’s fuzzy integral to compute the distance between records. The first approach uses a linear optimization problem which determines the optimal fuzzy measure for the linkage. While, the second approach is a kind of gradient algorithm with constraints for the fuzzy measures’ identification. We show the advantages and drawbacks of both algorithms and also in which situations they will work better.

URLhttp://www.springerlink.com/content/2373816u384j86m8/