Familiarisation: Restructuring layouts with visual learning models

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorTodi, Kashyapen_US
dc.contributor.authorJokinen, Jussien_US
dc.contributor.authorLuyten, Krisen_US
dc.contributor.authorOulasvirta, Anttien_US
dc.contributor.departmentDepartment of Communications and Networkingen
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.groupauthorUser Interfacesen
dc.contributor.organizationHasselt Universityen_US
dc.date.accessioned2018-09-06T10:16:16Z
dc.date.available2018-09-06T10:16:16Z
dc.date.issued2018-03-05en_US
dc.description| openaire: EC/H2020/637991/EU//COMPUTED
dc.description.abstractIn domains where users are exposed to large variations in visuo-spatial features among designs, they often spend excess time searching for common elements (features) in familiar locations. This paper contributes computational approaches to restructuring layouts such that features on a new, unvisited interface can be found quicker. We explore four concepts of familiarisation, inspired by the human visual system (HVS), to automatically generate a familiar design for each user. Given a history of previously visited interfaces, we restructure the spatial layout of the new (unseen) interface with the goal of making its elements more easily found. Familiariser is a browser-based implementation that automatically restructures webpage layouts based on the visual history of the user. Our evaluation with users provides first evidence favouring familiarisation.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.extent547-558
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTodi, K, Jokinen, J, Luyten, K & Oulasvirta, A 2018, Familiarisation : Restructuring layouts with visual learning models . in IUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces . vol. Part F135193, ACM, pp. 547-558, International Conference on Intelligent User Interfaces, Tokyo, Japan, 07/03/2018 . https://doi.org/10.1145/3172944.3172949en
dc.identifier.doi10.1145/3172944.3172949en_US
dc.identifier.isbn9781450349451
dc.identifier.otherPURE UUID: 537e00e9-49be-4c03-b1e4-9c17c17b3c52en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/537e00e9-49be-4c03-b1e4-9c17c17b3c52en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85045467599&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/19265643/FamiliarisationIUI2018.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/33853
dc.identifier.urnURN:NBN:fi:aalto-201809064964
dc.language.isoenen
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/637991/EU//COMPUTEDen_US
dc.relation.ispartofInternational Conference on Intelligent User Interfacesen
dc.relation.ispartofseriesIUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfacesen
dc.relation.ispartofseriesVolume Part F135193en
dc.rightsopenAccessen
dc.subject.keywordAdaptive user interfacesen_US
dc.subject.keywordComputational designen_US
dc.subject.keywordGraphical layoutsen_US
dc.subject.keywordVisual searchen_US
dc.titleFamiliarisation: Restructuring layouts with visual learning modelsen
dc.typeA4 Artikkeli konferenssijulkaisussafi
dc.type.versionpublishedVersion

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