Assessing Deduplication and Data Linkage Quality: What to Measure?

dc.contributor.authorChristen, Peter
dc.contributor.authorGoiser, Karl
dc.coverage.spatialSydney Australia
dc.date.accessioned2015-12-13T23:00:32Z
dc.date.available2015-12-13T23:00:32Z
dc.date.createdDecember 5 2005
dc.date.issued2005
dc.date.updated2016-02-24T09:46:55Z
dc.description.abstractDeduplicating one data set or linking several data sets are increasingly important tasks in the data preparation steps of many data mining projects. The aim of such linkages is to match all records relating to the same entity. Research interest in this ar
dc.identifier.isbn1863657169
dc.identifier.urihttp://hdl.handle.net/1885/84167
dc.publisherUniversity of Technology Sydney
dc.relation.ispartofseriesAustralasian Data Mining Conference (AusDM 2005)
dc.sourceProceedings of the 4th Australasian Data Mining Conference
dc.source.urihttp://www.togawear.com/ausdm05/
dc.subjectKeywords: Data preparation; Database research; De duplications; Pair comparisons; Pre-processing; Quality measures; Record linkage; Research interests; Artificial intelligence; Data mining; Data handling Data integration and matching; Data mining pre-processing; Data or record linkage; Deduplication; Quality measures
dc.titleAssessing Deduplication and Data Linkage Quality: What to Measure?
dc.typeConference paper
local.bibliographicCitation.startpage16
local.contributor.affiliationChristen, Peter, College of Engineering and Computer Science, ANU
local.contributor.affiliationGoiser, Karl, College of Engineering and Computer Science, ANU
local.contributor.authoruidChristen, Peter, u4021539
local.contributor.authoruidGoiser, Karl, u4139857
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationMigratedxPub12432
local.identifier.scopusID2-s2.0-84884345501
local.type.statusPublished Version

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