In this work we propose a novel approach to music recommendation based exclusively on editorial metadata. To this end, we propose to use a public database of music releases Discogs.com, which contains extensive information about artists, their releases and record labels. We rely on an explicit set of music tracks provided by the user as evidence of his/her music preferences to construct a user profile suitable for distance-based music recommendation. We evaluate the proposed method against two purely ...
In this work we propose a novel approach to music recommendation based exclusively on editorial metadata. To this end, we propose to use a public database of music releases Discogs.com, which contains extensive information about artists, their releases and record labels. We rely on an explicit set of music tracks provided by the user as evidence of his/her music preferences to construct a user profile suitable for distance-based music recommendation. We evaluate the proposed method against two purely metadata-based approaches and one approach partially based on audio content in a listening experiment with 27 participants. The results of subjective evaluation show that the proposed method is competitive to the state-of-the-art recommenders based on commercial metadata, while being easily implemented relying only on open public data.
+
