{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:28:07Z","timestamp":1774434487796,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":41,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["V579"],"award-info":[{"award-number":["V579"]}],"id":[{"id":"10.13039\/501100002428","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1145\/3151848.3151849","type":"proceedings-article","created":{"date-parts":[[2018,1,23]],"date-time":"2018-01-23T13:26:49Z","timestamp":1516714009000},"page":"74-81","source":"Crossref","is-referenced-by-count":4,"title":["Introducing Global and Regional Mainstreaminess for Improving Personalized Music Recommendation"],"prefix":"10.1145","author":[{"given":"Markus","family":"Schedl","sequence":"first","affiliation":[{"name":"Johannes Kepler University, Linz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christine","family":"Bauer","sequence":"additional","affiliation":[{"name":"Johannes Kepler University, Linz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/3151848.3151849-1","doi-asserted-by":"crossref","unstructured":"Hyung Jun Ahn. 2006. Utilizing Popularity Characteristics for Product Recommendation. International Journal of Electronic Commerce 11, 2 (2006), 59--80. http:\/\/www.jstor.org\/stable\/27751212","DOI":"10.2753\/JEC1086-4415110203"},{"key":"key-10.1145\/3151848.3151849-2","unstructured":"Christian Anderson. 2006. The long tail: Why the future of business is selling less of more. Hachette Books, New York, NY, USA."},{"key":"key-10.1145\/3151848.3151849-3","doi-asserted-by":"crossref","unstructured":"Sarah Baker, Andy Bennett, and Jodie Taylor. 2013. Redefining mainstream popular music. Routledge.","DOI":"10.4324\/9780203127858"},{"key":"key-10.1145\/3151848.3151849-4","unstructured":"Chumki Basu, Haym Hirsh, and William Cohen. 1998. Recommendation as classification: Using social and content-based information in recommendation. In Proceedings of the AAAI Conference on Artificial Intelligence. American Association Intelligence, 714--720."},{"key":"key-10.1145\/3151848.3151849-5","doi-asserted-by":"crossref","unstructured":"Christine Bauer, Marta Kholodylo, and Christine Strauss. 2017. Music Recommender Systems: Challenges and Opportunities for Non-Superstar Artists. In Proceedings of 30th Bled eConference, Andreja Pucihar, Mirjana Kljaji&#263; Bor&#353;tnar, Christian Kittl, Pascal Ravesteijn, Roger Clarke, and Roger Bons (Eds.). University of Maribor Press, Bled, Slovenia, 21--32.","DOI":"10.18690\/978-961-286-043-1.3"},{"key":"key-10.1145\/3151848.3151849-6","doi-asserted-by":"crossref","unstructured":"Erik Brynjolfsson, Yu Hu, and Duncan Simester. 2011. Goodbye Pareto Principle, Hello Long Tail: The Effect of Search Costs on the Concentration of Product Sales. Management Science 57, 8 (2011), 1373--1386. http:\/\/www.jstor.org\/stable\/25835786","DOI":"10.1287\/mnsc.1110.1371"},{"key":"key-10.1145\/3151848.3151849-7","doi-asserted-by":"crossref","unstructured":"Oliver Budzinski and Julia Pannicke. 2017. Do preferences for pop music converge across countries?:Empirical evidence from the Eurovision Song Contest. Creative Industries Journal (2017), 1--20.","DOI":"10.1080\/17510694.2017.1332451"},{"key":"key-10.1145\/3151848.3151849-8","doi-asserted-by":"crossref","unstructured":"&#210;scar Celma. 2010. Music Recommendation and Discovery. Springer, Berlin, Heidelberg, Germany.","DOI":"10.1007\/978-3-642-13287-2"},{"key":"key-10.1145\/3151848.3151849-9","doi-asserted-by":"crossref","unstructured":"&#210;scar Celma and Pedro Cano. 2008. From Hits to Niches?: Or How Popular Artists Can Bias Music Recommendation and Discovery. In Proceedings of the v2Nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition (NETFLIX 2008). ACM, New York, NY, USA, Article 5, 8 pages. https:\/\/doi.org\/10.1145\/1722149.1722154","DOI":"10.1145\/1722149.1722154"},{"key":"key-10.1145\/3151848.3151849-10","doi-asserted-by":"crossref","unstructured":"Zhiyong Cheng and Jialie Shen. 2014. Just-for-Me: An Adaptive Personalization System for Location-Aware Social Music Recommendation. In Proceedings of the International Conference on Multimedia Retrieval (ICMR 2014). ACM, New York, NY, USA, 185:185--185:192. https:\/\/doi.org\/10.1145\/2578726.2578751","DOI":"10.1145\/2578726.2578751"},{"key":"key-10.1145\/3151848.3151849-11","doi-asserted-by":"crossref","unstructured":"Charles L.A. Clarke, Maheedhar Kolla, Gordon V. Cormack, Olga Vechtomova, Azin Ashkan, Stefan B&#252;ttcher, and Ian MacKinnon. 2008. Novelty and Diversity in Information Retrieval Evaluation. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2008). ACM, New York, NY, USA, 659--666. https:\/\/doi.org\/10.1145\/1390334.1390446","DOI":"10.1145\/1390334.1390446"},{"key":"key-10.1145\/3151848.3151849-12","doi-asserted-by":"crossref","unstructured":"Paolo Cremonesi, Franca Garzotto, Roberto Pagano, and Massimo Quadrana. 2014. Recommending without short head. In Proceedings of the 23rd International Conference on World Wide Web (WWW 2014). ACM, 245--246.","DOI":"10.1145\/2567948.2577286"},{"key":"key-10.1145\/3151848.3151849-13","unstructured":"Katayoun Farrahi, Markus Schedl, Andreu Vall, David Hauger, and Marko Tkal&#269;i&#269;. 2014. Impact of Listening Behavior on Music Recommendation. In Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014). 483--488."},{"key":"key-10.1145\/3151848.3151849-14","unstructured":"Bruce Ferwerda. 2016. Improving the User Experience of Music Recommender Systems Through Personality and Cultural Information. PhD. Johannes Kepler University Linz, Linz, Austria."},{"key":"key-10.1145\/3151848.3151849-15","unstructured":"David Hauger, Markus Schedl, Andrej Ko&#353;ir, and Marko Tkal&#269;i&#269;. 2013. The Million Musical Tweets Dataset: What Can We Learn From Microblogs. In Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013)."},{"key":"key-10.1145\/3151848.3151849-16","unstructured":"Xiao Hu, Jin Ha Lee, Kahyun Choi, and J.S. Downie. 2014. A Cross-cultural Study of Mood in K-pop Songs. In Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014). 217--238."},{"key":"key-10.1145\/3151848.3151849-17","doi-asserted-by":"crossref","unstructured":"Shinobu Kitayama and Hyekyung Park. 2007. Cultural shaping of self, emotion, and well-being: How does it work? Social and Personality Psychology Compass 1, 1 (2007), 202--222.","DOI":"10.1111\/j.1751-9004.2007.00016.x"},{"key":"key-10.1145\/3151848.3151849-18","unstructured":"Rajeev Kumar, B.K. Verma, and Shyam Sunder Rastogi. 2014. Social popularity based SVD++ recommender system. International Journal of Computer Applications 87, 14 (2014), 33--37."},{"key":"key-10.1145\/3151848.3151849-19","unstructured":"Audrey Laplante. 2014. Improving music recommender systems: what can we learn from research on music tags?. In Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014). 451--456."},{"key":"key-10.1145\/3151848.3151849-20","doi-asserted-by":"crossref","unstructured":"Greg Linden, Brent Smith, and Jeremy York. 2003. Amazon.com Recommendations: Item-to-Item Collaborative Filtering. IEEE Internet Computing 4, 1 (2003), 76--80.","DOI":"10.1109\/MIC.2003.1167344"},{"key":"key-10.1145\/3151848.3151849-21","doi-asserted-by":"crossref","unstructured":"Brian McFee, Luke Barrington, and Gert Lanckriet. 2012. Learning content similarity for music recommendation. IEEE transactions on audio, speech, and language processing 20, 8 (2012), 2207--2218.","DOI":"10.1109\/TASL.2012.2199109"},{"key":"key-10.1145\/3151848.3151849-22","doi-asserted-by":"crossref","unstructured":"Miquel Montaner, Beatriz L&#243;pez, and Josep Llu&#237;s de la Rosa. 2003. A taxonomy of recommender agents on the Internet. Artificial Intelligence Review 19, 4 (2003), 285--330.","DOI":"10.1023\/A:1022850703159"},{"key":"key-10.1145\/3151848.3151849-23","doi-asserted-by":"crossref","unstructured":"Martin Pichl, Eva Zangerle, and G&#252;nther Specht. 2015. Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name?. In Proceedings of the 15th IEEE International Conference on Data Mining Workshop (ICDM 15). IEEE, Piscataway, NJ, USA, 1360--1365.","DOI":"10.1109\/ICDMW.2015.145"},{"key":"key-10.1145\/3151848.3151849-24","unstructured":"Tim Pohle, Markus Schedl, Peter Knees, and Gerhard Widmer. 2006. Automatically Adapting the Structure of Audio Similarity Spaces. In Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals (LSAS 2006)."},{"key":"key-10.1145\/3151848.3151849-25","doi-asserted-by":"crossref","unstructured":"Francesco Ricci, Lior Rokach, and Bracha Shapira. 2015. Recommender Systems Handbook (2nd ed.). Springer, New York, NY.","DOI":"10.1007\/978-1-4899-7637-6"},{"key":"key-10.1145\/3151848.3151849-26","doi-asserted-by":"crossref","unstructured":"Paul Rutten. 1991. Local popular music on the national and international markets. Cultural Studies 5, 3 (1991), 294--305.","DOI":"10.1080\/09502389100490241"},{"key":"key-10.1145\/3151848.3151849-27","unstructured":"Ruslan Salakhutdinov and Andriy Mnih. 2007. Probabilistic Matrix Factorization. In Proceedings of the 20th International Conference on Neural Information Processing Systems (NIPS 2007). Curran Associates Inc., 1257--1264. http:\/\/dl.acm.org\/citation.cfm?id=2981562.2981720"},{"key":"key-10.1145\/3151848.3151849-28","doi-asserted-by":"crossref","unstructured":"Gerard Salton, Andrew Wong, and Chung-Shu Yang. 1975. A Vector Space Model for Automatic Indexing. Commun. ACM 18, 11 (1975), 613--620. https:\/\/doi.org\/10.1145\/361219.361220","DOI":"10.1145\/361219.361220"},{"key":"key-10.1145\/3151848.3151849-29","doi-asserted-by":"crossref","unstructured":"Markus Schedl. 2013. Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation. In Proceedings of International Conference on Advances in Mobile Computing & Multimedia (MoMM) (MoMM '13). ACM, New York, NY, USA, 3:3--3:9. https:\/\/doi.org\/10.1145\/2536853.2536856","DOI":"10.1145\/2536853.2536856"},{"key":"key-10.1145\/3151848.3151849-30","doi-asserted-by":"crossref","unstructured":"Markus Schedl. 2016. The LFM-1b Dataset for Music Retrieval and Recommendation. In Proceedings of the 17th ACM International Conference on Multimedia Retrieval (ICMR 2016). New York, NY, USA.","DOI":"10.1145\/2911996.2912004"},{"key":"key-10.1145\/3151848.3151849-31","doi-asserted-by":"crossref","unstructured":"Markus Schedl. 2017. Investigating country-specific music preferences and music recommendation algorithms with the LFM-1b dataset. International Journal of Multimedia Information Retrieval 6, 1 (2017), 71--84. https:\/\/doi.org\/10.1007\/s13735-017-0118-y","DOI":"10.1007\/s13735-017-0118-y"},{"key":"key-10.1145\/3151848.3151849-32","doi-asserted-by":"crossref","unstructured":"Markus Schedl and Christine Bauer. 2017. Distance- and Rank-based Music Mainstreaminess Measurement. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (July 9-12, 2017) (UMAP 2017). ACM, New York, NY, USA, 364--367. https:\/\/doi.org\/10.1145\/3099023.3099098","DOI":"10.1145\/3099023.3099098"},{"key":"key-10.1145\/3151848.3151849-33","doi-asserted-by":"crossref","unstructured":"Markus Schedl, Emilia G&#243;mez, and Juli&#225;n Urbano. 2014. Music Information Retrieval: Recent Developments and Applications. Foundations and Trends in Information Retrieval 8, 2--3 (2014), 127--261. https:\/\/doi.org\/10.1561\/1500000042","DOI":"10.1561\/1500000042"},{"key":"key-10.1145\/3151848.3151849-34","doi-asserted-by":"crossref","unstructured":"Markus Schedl and David Hauger. 2015. Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty. In Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015).","DOI":"10.1145\/2766462.2767763"},{"key":"key-10.1145\/3151848.3151849-35","unstructured":"Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov, and Marius Kaminskas. 2015. Recommender Systems Handbook (2nd ed.). Springer, New York, NY, USA, Chapter Music Recommender Systems, 453--492."},{"key":"key-10.1145\/3151848.3151849-36","doi-asserted-by":"crossref","unstructured":"Catherine J. Stevens. 2012. Music Perception and Cognition: A Review of Recent Cross-Cultural Research. Topics in Cognitive Science 4, 4 (2012), 653--667.","DOI":"10.1111\/j.1756-8765.2012.01215.x"},{"key":"key-10.1145\/3151848.3151849-37","unstructured":"Gabriel Vigliensoni and Ichiro Fujinaga. 2016. Automatic music recommendation systems: do demographic, profiling, and contextual features improve their performance?. In Proceedings of the 17th International Society for Music Information Retrieval Conference (August 7-11, 2016) (ISMIR 2016). 94--100."},{"key":"key-10.1145\/3151848.3151849-38","unstructured":"Linxing Xiao, Lie Lu, Frank Seide, and Jie Zhou. 2009. Learning a music similarity measure on automatic annotations with application to playlist generation. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (April 19-24, 2009) (ICASSP 2009). IEEE, 1885--1888."},{"key":"key-10.1145\/3151848.3151849-39","doi-asserted-by":"crossref","unstructured":"Yan Yan, Tianlong Liu, and Zhenyu Wang. 2015. A Music Recommendation Algorithm Based on Hybrid Collaborative Filtering Technique. In 4th National Conference on Social Media Processing (November 16-17, 2015) (SMP 2015), Xi-chun Zhang, Maosong Sun, Zhenyu Wang, and Xuanjing Huang (Eds.). Springer, Singapore, 233--240. https:\/\/doi.org\/10.1007\/978-981-10-0080-5_23","DOI":"10.1007\/978-981-10-0080-5_23"},{"key":"key-10.1145\/3151848.3151849-40","doi-asserted-by":"crossref","unstructured":"JungAe Yang. 2016. Effects of Popularity-Based News Recommendations (\"Most-Viewed\") on Users' Exposure to Online News. Media Psychology 19, 2 (2016), 243--271. https:\/\/doi.org\/10.1080\/15213269.2015.1006333","DOI":"10.1080\/15213269.2015.1006333"},{"key":"key-10.1145\/3151848.3151849-41","doi-asserted-by":"crossref","unstructured":"Yuan Cao Zhang, Diarmuid &#211;. Seaghdha, Daniele Quercia, and Tamas Jambor. 2012. Auralist: Introducing Serendipity into Music Recommendation. In Proceedings of the 5th ACM International Conference on Web Search and Data Mining (WSDM 2012). Seattle, WA, USA.","DOI":"10.1145\/2124295.2124300"}],"event":{"name":"the 15th International Conference","location":"Salzburg, Austria","acronym":"MoMM2017","number":"15","sponsor":["@WAS, International Organization of Information Integration and Web-based Applications and Services","Johannes Kepler University, Linz, Austria"],"start":{"date-parts":[[2017,12,4]]},"end":{"date-parts":[[2017,12,6]]}},"container-title":["Proceedings of the 15th International Conference on Advances in Mobile Computing &amp; Multimedia - MoMM2017"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3151848.3151849","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3151849&ftid=1942077&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:11:06Z","timestamp":1750212666000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3151848.3151849"}},"subtitle":[],"proceedings-subject":"Advances in Mobile Computing & Multimedia","short-title":[],"issued":{"date-parts":[[2017]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1145\/3151848.3151849","relation":{},"subject":[],"published":{"date-parts":[[2017]]}}}