A Content-based System for Music Recommendation and Visualization of User Preferences Working on Semantic Notions

TitleA Content-based System for Music Recommendation and Visualization of User Preferences Working on Semantic Notions
Publication TypeConference Paper
Year of Publication2011
Conference Name9th International Workshop on Content-based Multimedia Indexing
AuthorsBogdanov, D., Haro M., Fuhrmann F., Xambó A., Gómez E., & Herrera P.
Conference Start Date13/06/2011
Conference LocationMadrid, Spain
AbstractThe amount of digital music has grown unprecedentedly during the last years and requires the development of effective methods for search and retrieval. In particular, content-based reference elicitation for music recommendation is a challenging problem that is effectively addressed in this paper. We present a system which automatically generates recommendations and visualizes a user’s musical preferences, given her/his accounts on popular online music services. Using these services, the system retrieves a set of tracks preferred by a user, and further computes a semantic description of musical preferences based on raw audio information. For the audio analysis we used the capabilities of the Canoris API. Thereafter, the system generates music recommendations, using a semantic music similarity measure, and a user’s preference visualization, mapping semantic descriptors to visual elements.
preprint/postprint documenthttp://mtg.upf.edu/files/publications/Bogdanov-et-al-CBMI2011.pdf
intranet