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2007

Automatic Generation of Social Tags for Music Recommendation

11 years 11 months ago
Automatic Generation of Social Tags for Music Recommendation
Social tags are user-generated keywords associated with some resource on the Web. In the case of music, social tags have become an important component of “Web2.0” recommender systems, allowing users to generate playlists based on use-dependent terms such as chill or jogging that have been applied to particular songs. In this paper, we propose a method for predicting these social tags directly from MP3 files. Using a set of boosted classifiers, we map audio features onto social tags collected from the Web. The resulting automatic tags (or autotags) furnish information about music that is otherwise untagged or poorly tagged, allowing for insertion of previously unheard music into a social recommender. This avoids the ”cold-start problem” common in such systems. Autotags can also be used to smooth the tag space from which similarities and recommendations are made by providing a set of comparable baseline tags for all tracks in a recommender system.
Douglas Eck, Paul Lamere, Thierry Bertin-Mahieux,
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NIPS
Authors Douglas Eck, Paul Lamere, Thierry Bertin-Mahieux, Stephen Green
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