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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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Personalized Retrieval and Browsing of Classical Music and Supporting Multimedia Material., , , and . ICMR, page 393-396. ACM, (2016)The LFM-1b Dataset for Music Retrieval and Recommendation.. ICMR, page 103-110. ACM, (2016)Exploring Music Diversity Needs Across Countries., , , and . UMAP, page 287-288. ACM, (2016)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)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)Personality & Emotional States: Understanding Users' Music Listening Needs., , and . UMAP Workshops, volume 1388 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)PHENICX: Innovating the classical music experience., , and . ICME Workshops, page 1-4. IEEE Computer Society, (2015)Country of origin determination via Web mining techniques., , and . ICME, page 1451-1456. IEEE Computer Society, (2010)