Familiarisation

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Journal Title
Journal ISSN
Volume Title
Conference article in proceedings
Date
2018-03-05
Major/Subject
Mcode
Degree programme
Language
en
Pages
12
547-558
Series
IUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces, Volume Part F135193
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.
Description
| openaire: EC/H2020/637991/EU//COMPUTED
Keywords
Adaptive user interfaces, Computational design, Graphical layouts, Visual search
Other note
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