Inference of User Context from GPS Logs for Proactive Recommender Systems

With the increasing popularity of smartphones, the wide availability of mobile Internet and the higher computational power of mobile devices, new types of applications are now possible. It is important to provide a smooth user experience by facilitating the interaction with the device. To do so, the goal of the work is support proactive recommendations on the mobile device. In order to determine the best point in time for a recommendation, various context information needs to be taken into account. One interesting aspect is determining the current user activity, e.g. whether the user is walking or not. In this paper, we present an algorithm that runs online on a smartphone and analyzes the user activity based on GPS data.