Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content
Yashar Deldjoo, Markus Schedl, Mehdi Elahi · 2019
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.