Efficient Matching in a Context-Aware Event Notification System for Mobile Users

As the amount of information accessible to mobile users increases, the need for an effective system to deliver relevant information to users also increases. Event-based systems can help users deal with vast amounts of changing information, but existing approaches do not adequately address the needs of the growing number of mobile users. To address these needs, we built an automatic, personalized, context-aware event notification system that efficiently and flexibly matches users and events while automatically learning individual user preferences for the current context. We developed a concise and expressive multi–content graph event model for describing events and user interests, and a fast and efficient algorithm for matching events according to this model. In this paper we describe our event model and matching algorithm and present evaluation results illustrating the performance of our system.