The Internet, which brought the most innovative improvement on information society, web recommendation systems based on web usage mining try to mine user’s behavior patters from web access logs, and recommend pages or suggestions to the user by matching the user’s browsing behavior with the mined historical behavior patterns. In this paper we propose a recommendation framework that considers different application status and various contexts of each user. We successfully implemented the proposed framework and show how this system can improve the overall quality of web recommendations.