Personalized Knowledge Service for Smart Cell-Phone Based on Usage: Conceptual Model and Intention Prediction Algorithm

Smart cell-phones include many advanced applications and services that allow their users to achieve various useful goals. However, many users face difficulties when upgrading their cell-phone devices to more advanced ones, partially because their applications include more complex patterns of use for achieving the users’ goals. We present a conceptual framework that aims to help overcoming usage barrier by providing smart cell-phone users a personalized knowledge service. The framework is based on the utilization of task models and on the tracking and analyzing the usage of the applications included in the smart cell-phone, that enable to construct user stereotypes and suggest personalized help according to their usage patterns. It is assumed that the system monitors the usage patterns of the user, thus enabling dynamic update of his/her belonging to a stereotype. The user can override the suggestions and navigate independently in order to find the required knowledge. This paper describes a method to model smart cell-phone applications, a software tool that enables a modeler to create task models for such applications, and an algorithm for analyzing the usage of mobile phone applications.