Markus Schedl

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Peter KneesFaculty of Informatics, TU WienVerified email at tuwien.ac.at
Gerhard WidmerProfessor of Computer Science, Johannes Kepler University LinzVerified email at jku.at
Marko TkalcicUniversity of PrimorskaVerified email at famnit.upr.si
Bruce FerwerdaAssistant Professor, Jönköping UniversityVerified email at ju.se
Bogdan IonescuPolitehnica University of BucharestVerified email at upb.ro
Yashar DeldjooAssistant Professor of Computer Science, Polytechnic University of Bari, ItalyVerified email at acm.org
Andreu VallJohannes Kepler UniversityVerified email at jku.at
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Julián UrbanoTU DelftVerified email at tudelft.nl
Hamid Eghbal-zadehInstitute of Computational Perception & LIT AI Lab, Johannes Kepler UniversityVerified email at jku.at
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
Christine BauerUtrecht UniversityVerified email at uu.nl
Cynthia C. S. LiemAssistant Professor, Multimedia Computing Group, Delft University of TechnologyVerified email at tudelft.nl
Sebastian BöckenliteAIVerified email at enlite.ai
Arthur FlexerJohannes Kepler University LinzVerified email at jku.at
Mats SjöbergMachine learning specialist at CSCVerified email at csc.fi
Marcin SkowronResearch Scientist | Austrian Research Institute for AI | Johannes Kepler UniversityVerified email at ofai.at
Hamed ZamaniAssistant Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Ching-Wei ChenSpotifyVerified email at cwlabs.com

Markus Schedl

Professor at Johannes Kepler University Linz, Institute of Computational Perception

Verified email at jku.at - Homepage

Recommendation Systems User Modeling Multimedia Music Information Retrieval Data Analysis


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Music recommender systems M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas Recommender systems handbook, 453-492, 2015	279*	2015
Music information retrieval: Recent developments and applications M Schedl, E Gómez Gutiérrez, J Urbano Foundations and Trends in Information Retrieval. 2014 Sept 12; 8 (2-3): 127-261., 2014	219	2014
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	162	2018
Polyphonic piano note transcription with recurrent neural networks S Böck, M Schedl 2012 IEEE international conference on acoustics, speech and signal …, 2012	162	2012
Evaluating the Online Capabilities of Onset Detection Methods. S Böck, F Krebs, M Schedl ISMIR, 49-54, 2012	145	2012
The neglected user in music information retrieval research M Schedl, A Flexer, J Urbano Journal of Intelligent Information Systems 41 (3), 523-539, 2013	141	2013
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	134	2006
A survey of music similarity and recommendation from music context data P Knees, M Schedl ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013	129	2013
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	128	2007
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	113	2016
The lfm-1b dataset for music retrieval and recommendation M Schedl Proceedings of the 2016 ACM on International Conference on Multimedia …, 2016	109	2016
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	101	2013
On Rhythm and General Music Similarity. T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer ISMIR, 525-530, 2009	100	2009
Local and global scaling reduce hubs in space. D Schnitzer, A Flexer, M Schedl, G Widmer Journal of Machine Learning Research 13 (10), 2012	99	2012
Enhanced beat tracking with context-aware neural networks S Böck, M Schedl Proc. Int. Conf. Digital Audio Effects, 135-139, 2011	95	2011
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	94	2010
Predicting personality traits with instagram pictures B Ferwerda, M Schedl, M Tkalcic Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015	91	2015
Using instagram picture features to predict users’ personality B Ferwerda, M Schedl, M Tkalcic International Conference on Multimedia Modeling, 850-861, 2016	82	2016
The million musical tweets dataset: What can we learn from microblogs D Hauger, M Schedl, A Košir, M Tkalcic Proc. ISMIR, 189-194, 2013	82	2013
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	79	2015

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