The most common interfaces of human-computer interaction are graphical interfaces. Thus, usability of those interfaces is of importance for research and industry. However, interfaces become more and more dynamic in appearance and functionality, why analysis of usability is a complex task. We propose a visual approach to identify changes in an interface as stimulus, in order to cluster user experiences of multiple users. We have trained a classifier that takes visual features from the video recording of an interaction with an interface and decides about visual changes. We use the visual changes to split and merge the user experiences of multiple users into representations that comprehend coherent visual states of an interface. We demonstrate our approach for popular Web sites and report about classification performance for learning and classification within and across Web sites. Furthermore, we apply our classifier in a practical example to cluster user experiences on a Web page and demonstrate the feasibility of our approach.
04.04.2019 - 10:15