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The State of the Art in Integrating Machine Learning into Visual Analytics

dc.contributor.authorEndert, A.
dc.contributor.authorRibarsky, W.
dc.contributor.authorTurkay, C.
dc.contributor.authorWong, B. W.
dc.contributor.authorNabney, I.
dc.contributor.authorDíaz Blanco, Ignacio 
dc.contributor.authorRossi, F.
dc.date.accessioned2017-06-29T09:12:47Z
dc.date.available2017-06-29T09:12:47Z
dc.date.issued2017
dc.identifier.citationComputer Graphics Forum (2017); doi:10.1111/cgf.13092
dc.identifier.issn0167-7055
dc.identifier.urihttp://hdl.handle.net/10651/43038
dc.description.abstractVisual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning and data visualization is still under-explored. This state-of-the-art report presents a summary of the progress that has been made by highlighting and synthesizing select research advances. Further, it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions
dc.description.sponsorshipPublicación realizada en el marco del proyecto DPI2015-69891-C2-2-R, financiado por el Ministerio de Economía y Competitividad (MINECO), Programa Estatal de I+D+i Orientada a los Retos de la Sociedad y por el Fondo Europeo de Desarrollo Regional (FEDER) "Una manera de hacer Europa"
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofComputer Graphics Forum
dc.rights© 2017 Wiley
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInformation visualization
dc.subjectData mining
dc.titleThe State of the Art in Integrating Machine Learning into Visual Analyticseng
dc.typejournal article
dc.identifier.doi10.1111/cgf.13092
dc.relation.projectIDDPI2015-69891-C2-2-R
dc.relation.publisherversionhttp://dx.doi.org/10.1111/cgf.13092
dc.rights.accessRightsopen access
dc.type.hasVersionSMUR


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