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dc.contributor.authorRandall, Sean
dc.contributor.authorBoyd, James
dc.contributor.authorFerrante, Anna
dc.contributor.authorBauer, J.
dc.contributor.authorSemmens, James
dc.date.accessioned2017-01-30T10:29:23Z
dc.date.available2017-01-30T10:29:23Z
dc.date.created2014-07-03T20:00:23Z
dc.date.issued2014
dc.date.submitted2014-07-04
dc.identifier.citationRandall, S. and Boyd, J. and Ferrante, A. and Bauer, J. and Semmens, J. 2014. Use of graph theory measures to identify errors in record linkage. Computer Methods and Programs in Biomedicine. 115 (2): pp. 55-63.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/3205
dc.identifier.doi10.1016/j.cmpb.2014.03.008
dc.description.abstract

Ensuring high linkage quality is important in many record linkage applications. Current methods for ensuring quality are manual and resource intensive. This paper seeks to determine the effectiveness of graph theory techniques in identifying record linkage errors. A range of graph theory techniques was applied to two linked datasets, with known truth sets. The ability of graph theory techniques to identify groups containing errors was compared to a widely used threshold setting technique. This methodology shows promise; however, further investigations into graph theory techniques are required. The development of more efficient and effective methods of improving linkage quality will result in higher quality datasets that can be delivered to researchers in shorter timeframes.

dc.publisherElsevier Ireland Ltd
dc.subjectRecord linkage
dc.subjectGraph theory
dc.subjectData quality
dc.titleUse of graph theory measures to identify errors in record linkage
dc.typeJournal Article
dcterms.dateSubmitted2014-07-04
dcterms.source.volume115
dcterms.source.number2
dcterms.source.startPage55
dcterms.source.endPage63
dcterms.source.issn01692607
dcterms.source.titleComputer Methods and Programs in Biomedicine
curtin.digitool.pid199679
curtin.note

NOTICE: This is the author’s version of a work that was accepted for publication in Computer Methods and Programs in Biomedicine. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Methods and Programs in Biomedicine, Vol. 115, Issue 2. (2014). doi: 10.1016/j.cmpb.2014.03.008

curtin.pubStatusPublished
curtin.department
curtin.identifier.scriptidPUB-HEA-CPH-PB-83047
curtin.accessStatusOpen access


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