20th International Conference on MultiMedia Modeling (MMM 2014)
Sprache des Tagungstitel:
Current advances in music recommendation underline the
importance of multimodal and user-centric approaches in order to transcend
limits imposed by methods that solely use audio, web, or collaborative
filtering data. We propose several hybrid music recommendation
algorithms that combine information on the music content, the music
context, and the user context, in particular integrating geospatial notions
of similarity. To this end, we use a novel standardized data set of music
listening activities inferred from microblogs (MusicMicro) and state-ofthe-
art techniques to extract audio features and contextual web features.
The multimodal recommendation approaches are evaluated for the task
of music artist recommendation. We show that traditional approaches
(in particular, collaborative filtering) benefit from adding a user context
component, geolocation in this case.