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, 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.
Publications:
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Journal Article Kashyap Todi, Jussi Jokinen, Kris Luyten, Antti Oulasvirta. Individualising Graphical Layouts with Predictive Visual Search Models.
In ACM Transactions of Interactive Intelligent Systems (TIIS) Volume 10, Issue 1, Article 9 (August 2019).
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Full Paper Kashyap Todi, Jussi Jokinen, Kris Luyten, Antti Oulasvirta. Familiarisation: Restructuring Layouts with Visual Learning Models.
In IUI '18: Proceedings of the ACM Conference on Intelligent User Interfaces.
Slides from IUI 2018 (Tokyo, Japan):
