Activity centered Design of Smart Phone User Interface: Learning App Execution Patterns with Neural Network Model

The user interface design of smart phone is often too simple in logic that the taxonomy of tasks frequently performed is the only basis and the UI allow the user to add their favorite Apps as they want. However, with too many Apps available for smart phone users but not many of them are used frequently, the convenience of smart phone usage can and should be developed not just by the predefined functions but to maximize its UI usefulness from user's activity analysis. In this paper, we propose an intelligent method using BAM network to minimize searching for the frequently asked Apps by recognizing and learning user's signal to execute them. This is a form of activity-centered design to maximize user's convenience in user interface of a smart phone.