Predicting Genre Preferences from Cultural and Socio-Economic Factors for Music Retrieval

Author:

Skowron Marcin,Lemmerich Florian,Ferwerda Bruce,Schedl Markus

Publisher

Springer International Publishing

Reference13 articles.

1. Cheng, Z., Shen, J.: Just-for-me: an adaptive personalization system for location-aware social music recommendation. In: Proceedings of the 2014 ACM International Conference on Multimedia Retrieval, Glasgow, UK, April 2014

2. Ferwerda, B., Schedl, M.: Investigating the relationship between diversity in music consumption behavior and cultural dimensions: a cross-country analysis. In: Workshop on S, Halifax, Canada, July 2016

3. Ferwerda, B., Vall, A., Tkalčič, M., Schedl, M.: Exploring music diversity needs across countries. In: User Modeling, Adaptation and Personalization, Halifax, Canada (2016)

4. Hauger, D., Schedl, M., Košir, A., Tkalčič, M.: The million musical tweets dataset: what can we learn from microblogs. In: Proceedings of the 14th International Society for Music Information Retrieval Conference, Brazil, November 2013

5. Hofstede, G., Hofstede, G.J., Minkov, M.: Cultures and Organizations: Software of the Mind, 3rd edn. McGraw-Hill, New York (2010)

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