Markus Schedl
Markus Schedl
Professor at Johannes Kepler University Linz, Institute of Computational Perception
Verifierad e-postadress på jku.at - Startsida
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Music recommender systems
M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas
Recommender systems handbook, 453-492, 2015
230*2015
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
1682014
Polyphonic piano note transcription with recurrent neural networks
S Böck, M Schedl
2012 IEEE international conference on acoustics, speech and signal …, 2012
1382012
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
1232006
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
1192007
The neglected user in music information retrieval research
M Schedl, A Flexer, J Urbano
Journal of Intelligent Information Systems 41 (3), 523-539, 2013
1112013
A survey of music similarity and recommendation from music context data
P Knees, M Schedl
ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013
1102013
Evaluating the Online Capabilities of Onset Detection Methods.
S Böck, F Krebs, M Schedl
ISMIR, 49-54, 2012
1082012
Local and global scaling reduce hubs in space
D Schnitzer, A Flexer, M Schedl, G Widmer
Journal of Machine Learning Research 13 (Oct), 2871-2902, 2012
922012
On Rhythm and General Music Similarity.
T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer
ISMIR, 525-530, 2009
912009
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 (2), 95-116, 2018
812018
Using block-level features for genre classification, tag classification and music similarity estimation
K Seyerlehner, M Schedl, T Pohle, P Knees
Submission to Audio Music Similarity and Retrieval Task of MIREX 2010, 2010
812010
The lfm-1b dataset for music retrieval and recommendation
M Schedl
Proceedings of the 2016 ACM on International Conference on Multimedia …, 2016
772016
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
762013
Enhanced beat tracking with context-aware neural networks
S Böck, M Schedl
Proc. Int. Conf. Digital Audio Effects, 135-139, 2011
742011
The million musical tweet dataset: what we can learn from microblogs
D Hauger, M Schedl, A Košir, M Tkalčič
International Society for Music Information Retrieval, 2013
732013
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
722016
Combining audio-based similarity with web-based data to accelerate automatic music playlist generation
P Knees, T Pohle, M Schedl, G Widmer
Proceedings of the 8th ACM international workshop on Multimedia information …, 2006
682006
Predicting personality traits with instagram pictures
B Ferwerda, M Schedl, M Tkalcic
Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015
672015
Personality traits predict music taxonomy preferences
B Ferwerda, E Yang, M Schedl, M Tkalcic
Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human …, 2015
652015
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Artiklar 1–20