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Introducing global and regional mainstreaminess for improving personalized music recommendation

, and . 15th International Conference on Advances in Mobile Computing & Multimedia (MoMM2017), page 74-81. New York, NY, USA, ACM, (December 2017)Best Paper Award.
DOI: 10.1145/3151848.3151849

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Investigating Web-Based Approaches to Revealing Prototypical Music Artists in Genre Taxonomies., , and . ICDIM, page 519-524. IEEE, (2006)Improving Prototypical Artist Detection by Penalizing Exorbitant Popularity., , and . CMMR, volume 3902 of Lecture Notes in Computer Science, page 196-200. Springer, (2005)Modeling Popularity and Temporal Drift of Music Genre Preferences., , and . Trans. Int. Soc. Music. Inf. Retr., 3 (1): 17-30 (2020)The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study., , and . CoRR, (2019)Music Information Retrieval: Recent Developments and Applications., , and . Found. Trends Inf. Retr., 8 (2-3): 127-261 (2014)Supervised and Unsupervised Web Document Filtering Techniques to Improve Text-Based Music Retrieval., , , , and . ISMIR, page 543-548. International Society for Music Information Retrieval, (2010)Augmenting Text-based Music Retrieval with Audio Similarity: Advantages and Limitations., , , , , and . ISMIR, page 579-584. International Society for Music Information Retrieval, (2009)Multiple Lyrics Alignment: Automatic Retrieval of Song Lyrics., , and . ISMIR, page 564-569. (2005)Intelligent User Interfaces for Social Music Discovery and Exploration of Large-scale Music Repositories.. HUMANIZE@IUI, page 7-11. ACM, (2017)Hybrid retrieval approaches to geospatial music recommendation., and . SIGIR, page 793-796. ACM, (2013)