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Extracted information quality, a comparative study in high and low dimensions

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dc.citation.journalTitleInternational Journal Of Business Intelligence And Data Mining
dc.contributor.authorAriza-Jimenez L.
dc.contributor.authorVilla, LF
dc.contributor.authorPinel N.
dc.contributor.authorLucia Quintero M, O.
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupBiodiversidad, Evolución y Conservaciónspa
dc.date.accessioned2021-03-23T19:52:12Z
dc.date.available2021-03-23T19:52:12Z
dc.date.issued2020-12-11
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=13658
dc.identifier.issn17438187
dc.identifier.issn17438195
dc.identifier.urihttps://hdl.handle.net/10784/26766
dc.language.isoeng
dc.publisherInderscience Enterprises Ltd.
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1743-8187
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.localAcceso abierto
dc.sourceInternational Journal Of Business Intelligence And Data Mining
dc.titleExtracted information quality, a comparative study in high and low dimensions
dc.typeinfo:eu-repo/semantics/article
dc.type.coarversionhttp://purl.org/coar/resource_type/c_6501
dc.type.localArtículospa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTREF
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication

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