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Markus Schedl
Markus Schedl
Professor at Johannes Kepler University Linz, Institute of Computational Perception
Verified email at jku.at - Homepage
Title
Cited by
Cited by
Year
Music recommender systems
M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas
Recommender systems handbook, 453-492, 2015
450*2015
Current challenges and visions in music recommender systems research
M Schedl, H Zamani, CW Chen, Y Deldjoo, M Elahi
International Journal of Multimedia Information Retrieval 7, 95-116, 2018
3502018
Music information retrieval: Recent developments and applications
M Schedl, E Gómez, J Urbano
Foundations and Trends® in Information Retrieval 8 (2-3), 127-261, 2014
3472014
The LFM-1b Dataset for Music Retrieval and Recommendation
M Schedl
Proceedings of the 2016 ACM on international conference on multimedia …, 2016
2132016
Polyphonic piano note transcription with recurrent neural networks
S Böck, M Schedl
2012 IEEE international conference on acoustics, speech and signal …, 2012
1922012
A survey of music similarity and recommendation from music context data
P Knees, M Schedl
ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013
1912013
Evaluating the Online Capabilities of Onset Detection Methods
S Böck, F Krebs, M Schedl
ISMIR, 49-54, 2012
1822012
Fusing social media cues: personality prediction from twitter and instagram
M Skowron, M Tkalčič, B Ferwerda, M Schedl
Proceedings of the 25th international conference companion on world wide web …, 2016
1792016
The neglected user in music information retrieval research
M Schedl, A Flexer, J Urbano
Journal of Intelligent Information Systems 41 (3), 523-539, 2013
1752013
Recommender systems leveraging multimedia content
Y Deldjoo, M Schedl, P Cremonesi, G Pasi
ACM Computing Surveys (CSUR) 53 (5), 1-38, 2020
1662020
Enhanced beat tracking with context-aware neural networks
S Böck, M Schedl
Proc. Int. Conf. Digital Audio Effects, 135-139, 2011
1422011
An innovative three-dimensional user interface for exploring music collections enriched
P Knees, M Schedl, T Pohle, G Widmer
Proceedings of the 14th ACM international conference on Multimedia, 17-24, 2006
1412006
The unfairness of popularity bias in music recommendation: A reproducibility study
D Kowald, M Schedl, E Lex
Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020
1392020
A music search engine built upon audio-based and web-based similarity measures
P Knees, T Pohle, M Schedl, G Widmer
Proceedings of the 30th annual international ACM SIGIR conference on …, 2007
1312007
Location-aware music recommendation using auto-tagging and hybrid matching
M Kaminskas, F Ricci, M Schedl
Proceedings of the 7th ACM Conference on Recommender Systems, 17-24, 2013
1292013
Predicting personality traits with instagram pictures
B Ferwerda, M Schedl, M Tkalcic
Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015
1272015
Local and global scaling reduce hubs in space.
D Schnitzer, A Flexer, M Schedl, G Widmer
Journal of Machine Learning Research 13 (10), 2012
1252012
Using instagram picture features to predict users’ personality
B Ferwerda, M Schedl, M Tkalcic
MultiMedia Modeling: 22nd International Conference, MMM 2016, Miami, FL, USA …, 2016
1182016
On Rhythm and General Music Similarity.
T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer
ISMIR, 525-530, 2009
1132009
Recsys challenge 2018: Automatic music playlist continuation
CW Chen, P Lamere, M Schedl, H Zamani
Proceedings of the 12th ACM Conference on Recommender Systems, 527-528, 2018
1082018
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