Markus Schedl

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	All	Since 2015
Citations	5717	3918
h-index	39	31
i10-index	139	99

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Co-authors

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 IonescuUniversity Politehnica of BucharestVerified email at upb.ro
Andreu VallJohannes Kepler UniversityVerified email at jku.at
Dominik SchnitzerAustrian Research Institute for Artificial Intelligence (OFAI)Verified email at ofai.at
Julián UrbanoTU DelftVerified email at tudelft.nl
Emilia GómezJoint Research Centre, European Commission and Music Technology Group, Universitat Pompeu FabraVerified email at upf.edu
Hamid Eghbal-zadehInstitute of Computational Perception & LIT AI Lab, Johannes Kepler UniversityVerified email at jku.at
Cynthia C. S. LiemAssistant Professor, Multimedia Computing Group, Delft University of TechnologyVerified email at tudelft.nl
Christine BauerUtrecht UniversityVerified email at uu.nl
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
Ionut MironicaAdobe ResearchVerified email at adobe.com
Yu-Gang JiangProfessor, Computer Science, Fudan University, ShanghaiVerified email at fudan.edu.cn
Jan SchlüterJohannes Kepler University Linz (JKU)Verified email at jku.at
Masataka GotoPrime Senior Researcher, National Institute of Advanced Industrial Science and Technology (AIST)Verified email at aist.go.jp
Marius KaminskasBeyond AnalysisVerified email at beyondanalysis.net

Markus Schedl

Professor at Johannes Kepler University Linz, Institute of Computational Perception

Verified email at jku.at - Homepage

Recommendation Systems User Modeling Multimedia Information Retrieval Machine Learning


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Music recommender systems M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas Recommender systems handbook, 453-492, 2015	272*	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	191	2014
Polyphonic piano note transcription with recurrent neural networks S Böck, M Schedl 2012 IEEE international conference on acoustics, speech and signal …, 2012	150	2012
Evaluating the Online Capabilities of Onset Detection Methods. S Böck, F Krebs, M Schedl ISMIR, 49-54, 2012	130	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	127	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	127	2006
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	123	2007
A survey of music similarity and recommendation from music context data P Knees, M Schedl ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013	122	2013
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	119	2018
Local and global scaling reduce hubs in space D Schnitzer, A Flexer, M Schedl, G Widmer The Journal of Machine Learning Research 13 (1), 2871-2902, 2012	96	2012
The lfm-1b dataset for music retrieval and recommendation M Schedl Proceedings of the 2016 ACM on International Conference on Multimedia …, 2016	94	2016
On Rhythm and General Music Similarity. T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer ISMIR, 525-530, 2009	92	2009
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	91	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	87	2013
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	85	2010
Enhanced beat tracking with context-aware neural networks S Böck, M Schedl Proc. Int. Conf. Digital Audio Effects, 135-139, 2011	82	2011
Predicting personality traits with instagram pictures B Ferwerda, M Schedl, M Tkalcic Proceedings of the 3rd Workshop on Emotions and Personality in Personalized …, 2015	81	2015
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	79	2013
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	74	2006
The MediaEval 2015 Affective Impact of Movies Task. M Sjöberg, Y Baveye, H Wang, VL Quang, B Ionescu, E Dellandréa, ... MediaEval, 2015	72	2015

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