Familiarisation: Restructuring layouts with visual learning models
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.author | Todi, Kashyap | en_US |
dc.contributor.author | Jokinen, Jussi | en_US |
dc.contributor.author | Luyten, Kris | en_US |
dc.contributor.author | Oulasvirta, Antti | en_US |
dc.contributor.department | Department of Communications and Networking | en |
dc.contributor.groupauthor | Helsinki Institute for Information Technology (HIIT) | en |
dc.contributor.groupauthor | User Interfaces | en |
dc.contributor.organization | Hasselt University | en_US |
dc.date.accessioned | 2018-09-06T10:16:16Z | |
dc.date.available | 2018-09-06T10:16:16Z | |
dc.date.issued | 2018-03-05 | en_US |
dc.description | | openaire: EC/H2020/637991/EU//COMPUTED | |
dc.description.abstract | In 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.version | Peer reviewed | en |
dc.format.extent | 12 | |
dc.format.extent | 547-558 | |
dc.format.mimetype | application/pdf | en_US |
dc.identifier.citation | Todi, 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/10.1145/3172944.3172949 | en |
dc.identifier.doi | 10.1145/3172944.3172949 | en_US |
dc.identifier.isbn | 9781450349451 | |
dc.identifier.other | PURE UUID: 537e00e9-49be-4c03-b1e4-9c17c17b3c52 | en_US |
dc.identifier.other | PURE ITEMURL: https://research.aalto.fi/en/publications/537e00e9-49be-4c03-b1e4-9c17c17b3c52 | en_US |
dc.identifier.other | PURE LINK: http://www.scopus.com/inward/record.url?scp=85045467599&partnerID=8YFLogxK | en_US |
dc.identifier.other | PURE FILEURL: https://research.aalto.fi/files/19265643/FamiliarisationIUI2018.pdf | en_US |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/33853 | |
dc.identifier.urn | URN:NBN:fi:aalto-201809064964 | |
dc.language.iso | en | en |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/637991/EU//COMPUTED | en_US |
dc.relation.ispartof | International Conference on Intelligent User Interfaces | en |
dc.relation.ispartofseries | IUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces | en |
dc.relation.ispartofseries | Volume Part F135193 | en |
dc.rights | openAccess | en |
dc.subject.keyword | Adaptive user interfaces | en_US |
dc.subject.keyword | Computational design | en_US |
dc.subject.keyword | Graphical layouts | en_US |
dc.subject.keyword | Visual search | en_US |
dc.title | Familiarisation: Restructuring layouts with visual learning models | en |
dc.type | A4 Artikkeli konferenssijulkaisussa | fi |
dc.type.version | publishedVersion |