Contextual adaptive user interface for Android devices

In this paper we propose a framework to adapt the user interface (UI) of mobile computing devices like smartphones or tablets, based on the context or scenario in which user is present, and incorporating learning from past user actions. This will allow the user to perform actions in minimal steps and also reduce the clutter. The user interface in question can include application icons, menus, buttons window positioning or layout, color scheme and so on. The framework profiles the user device usage pattern and uses machine learning algorithms to predict the best possible screen configuration with respect to the user context. The prediction will improve with time and will provide best user experience possible to the user. To predict the utility of our model, we measure average response times for a number of users to access certain applications randomly on a smartphone, and on that basis predict time saved by adapting the UI in this way.