Multimedia content recommendation engine with automatic inference of user preferences

We propose novel algorithms for automatically determining a user´s profile from his/her content usage history (profiling agent), and automatically filtering content according to the user´s profile (filtering agent). A fuzzy inference system is used to construct and periodically update the preferences of a user based on the user´s interactions with various types of content over an observation period. The proposed algorithms are designed to support an MPEG-7 or TV-anytime-compliant description framework, although they can also be utilized in any non-standard environment that provides structured descriptions of multimedia content.