Familiarisation: Restructuring Layouts with Visual Learning Models

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 previously unvisited interface can be found quicker. We explore four concepts of familiarisation, inspired by the human visual system (HVS), to automatically generate a representative (familiar) design for each user. Given a history of previously visited interfaces, we use this computed design to restructure the spatial layout of a new (unfamiliar) interface, with the goal of making features more easily findable. Familiariser is a browser-based implementation that automatically restructures webpage lay- outs based on the visual history of the user. Our evaluation with users provides first evidence favouring familiarisation.