A profiling engine for converged service delivery platforms

As services become increasingly personalized, mastering knowledge of user profiles is becoming a key requirement for service providers who hold large amounts of end user service consumption data. This paper describes a profiling engine that automatically learns user profiles (user preferences, interest domains, and behaviors) by aggregating traces on converged service delivery platforms such as Internet Protocol television (IPTV), mobile video, or IP Multimedia Subsystem (IMS). Such a profiling engine enables a wide range of personalized applications including targeted advertising, personalized portals, content recommenders, and social networking applications. (c) 2008 Alcatel-Lucent.