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How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data

dc.contributor.authorPappas, Ilias
dc.contributor.authorSharma, Kshitij
dc.contributor.authorMikalef, Patrick
dc.contributor.authorGiannakos, Michail
dc.date.accessioned2020-06-15T12:27:32Z
dc.date.available2020-06-15T12:27:32Z
dc.date.created2020-04-11T10:52:02Z
dc.date.issued2020
dc.identifier.citationLecture Notes in Computer Science (LNCS). 2020, 12067 429-440.en_US
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/11250/2658092
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titleHow Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Dataen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2020 Springer Verlagen_US
dc.subject.nsiVDP::Technology: 500::Information and communication technology: 550en_US
dc.source.pagenumber429-440en_US
dc.source.volume12067en_US
dc.source.journalLecture Notes in Computer Science (LNCS)en_US
dc.identifier.doihttps://doi.org/10.1007/978-3-030-45002-1
dc.identifier.cristin1805844
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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