Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content

We present a demo application of a web-based recommender systems that is powered by the 'Movie Genome', i.e., a rich semantic description of a movie's content, including state-of-The-Art audio and visual descriptors and metadata (genre and tags). The current version of the Movie Genome web application implements content-based filtering approaches. Due to its modular implementation and the free availability of its source code, it can be easily extended to various context-Aware and user-Aware scenarios. A personality questionnaire is already integrated into the web application, which allows it to also serve as testbed for personality-Aware recommendation algorithms.