User Interface Adaptation based on a Business Rules Management System and Machine Learning

Abstract

In ubiquitous computing environments, computers are embedded into everyday lives to provide information anywhere and at any time. Pervasive computing assists us in our everyday activities, operating invisibly in the background, regardless of our location or devices. Therefore, ubiquitous computing requires discovering new Human-Computer Interaction methods helping users to easily interact with ubiquitous systems whatever is the perceived context situation. However, designing context-aware applications that are able to adapt to context instability is a recurring problem that requires special attention from researchers in the HCI community. On the one hand, it is not trivial for a designer to specify how UIs should adapt, and on the other hand it is very hard to predict the context of use changes and accordingly to construct adaptive UIs that match users expectations. In this paper, we present a Model Driving Engineering (MDE) technique to design UIs that automatically adapt to the perceived context situation while the designer and eventually the end user still have full control over the adaptation during runtime. This technique is supported by a conceptual framework and a graphical tool that lower the threshold for designers as well as developers to design adaptive user interfaces, modelize context situations, edit adaptation rules and manage the adaptation process.