An effective named entity similarity metric for comparing data from multiple sources with varying syntax.
This article describes and demonstrates a named entity similarity metric developed for, and currently in use by, the FuzzyPhoto project. The presented metric is effective at comparing named entity data in and across syntaxless data schemas such as are often encountered in Gallery, Library, Archive,...
| Published in: | Digital Scholarship in the Humanities Vol. 32; no. 4; pp. 779 - 788 |
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| Main Authors: | , , |
| Format: | Article |
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Oxford University Press / USA
Dec2017
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=126069654&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 126069654 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Dec2017 vid: 32 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 126069654 10.1093/llc/fqw035 ppf: 779 ppct: 9 formats: fmt: @attributes: type: P size: 400KB tig: atl: An effective named entity similarity metric for comparing data from multiple sources with varying syntax. aug: au: Croft, David Brown, Stephen Coupland, Simon affil: School of Computing, Electronics and Maths, Coventry University, UK Knowledge Media and Design, De Montfort University, UK Centre for Computational Intelligence, De Montfort University, UK su: Fuzzy sets Syntax (Grammar) Schemas (Psychology) Schematism (Philosophy) Data transmission systems sug: subj: Fuzzy sets Syntax (Grammar) Schemas (Psychology) Schematism (Philosophy) Data transmission systems ab: This article describes and demonstrates a named entity similarity metric developed for, and currently in use by, the FuzzyPhoto project. The presented metric is effective at comparing named entity data in and across syntaxless data schemas such as are often encountered in Gallery, Library, Archive, and Museum collections. The efficiency of the approach was compared to an existing named entity similarity metric and is shown to be a significant improvement when comparing messy named entity data. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2017 holdings: @attributes: islocal: N |
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