Evolution of context-aware user profiles

Context-awareness and adaptation are key issues in mobile and ubiquitous computing. Applications on mobile devices use context information to adapt themselves to changing environments. User profiles play an important role in these systems as they serve as an individualization filter in a wide range of possible context adaptation parameters. In this paper we propose a modeling approach for the evolution of context-aware user profiles. A motivating scenario, the intelligent selection of a suitable medical expert in an emergency situation, shows the need for context-aware matching of user profiles. This is achieved by a similarity matching algorithm and reinforcement learning.