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A survey of music similarity and recommendation from music context data.

, and . ACM Trans. Multim. Comput. Commun. Appl., 10 (1): 2:1-2:21 (2013)

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Automatically Adapting the Structure of Audio Similarity Spaces, , , and . Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals, Athens, Greece, (2006)The Million Musical Tweet Dataset - What We Can Learn From Microblogs., , , and . ISMIR, page 189-194. (2013)Mining User Generated Data for Music Information Retrieval., , , and . Mining User Generated Content, Chapman and Hall/CRC, (2014)Three web-based heuristics to determine a person's or institution's country of origin., , , , and . SIGIR, page 801-802. ACM, (2010)A personality-based adaptive system for visualizing classical music performances., , , , , and . MMSys, page 15:1-15:7. ACM, (2016)Introduction to Intelligent Music Systems and Applications., , and . ACM TIST, 8 (2): 17:1-17:8 (2017)Exploring Music Artists via Descriptive Terms and Multimedia Content., and . SAMT, volume 5392 of Lecture Notes in Computer Science, page 137-148. Springer, (2008)Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features: Alleviating the Cold-Start Problem for Rare and Out-of-Set Songs., , , , and . DLRS@RecSys, page 46-54. ACM, (2017)Genre-based Analysis of Social Media Data on Music Listening Behavior: Are Fans of Classical Music Really Averse to Social Media?, and . WISMM, page 9-13. ACM, (2014)Personality Traits and Music Genres: What Do People Prefer to Listen To?, , and . UMAP, page 285-288. ACM, (2017)