| Music recommender systems M Schedl, P Knees, B McFee, D Bogdanov, M Kaminskas Recommender systems handbook, 453-492, 2015 | 213 | 2015 |
| A survey of music similarity and recommendation from music context data P Knees, M Schedl ACM Transactions on Multimedia Computing, Communications, and Applications …, 2013 | 213 | 2013 |
| Artist Classification with Web-Based Data. P Knees, E Pampalk, G Widmer ISMIR, 2004 | 163 | 2004 |
| 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 | 147 | 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 | 134 | 2007 |
| On Rhythm and General Music Similarity. T Pohle, D Schnitzer, M Schedl, P Knees, G Widmer ISMIR, 525-530, 2009 | 116 | 2009 |
| 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 (2), 3, 2010 | 99 | 2010 |
| Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections P Knees, Á Faraldo Pérez, H Boyer, R Vogl, S Böck, F Hörschläger, ... Proceedings of the 16th International Society for Music Information …, 2015 | 97 | 2015 |
| Drum Transcription via Joint Beat and Drum Modeling Using Convolutional Recurrent Neural Networks. R Vogl, M Dorfer, G Widmer, P Knees ISMIR, 150-157, 2017 | 96 | 2017 |
| Music similarity and retrieval: an introduction to audio-and web-based strategies P Knees, M Schedl Springer, 2016 | 92 | 2016 |
| Multi-Task Learning of Tempo and Beat: Learning One to Improve the Other. S Böck, MEP Davies, P Knees ISMIR, 486-493, 2019 | 87 | 2019 |
| 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 | 84 | 2006 |
| Oh Oh Oh Whoah! Towards Automatic Topic Detection In Song Lyrics. F Kleedorfer, P Knees, T Pohle Ismir, 287-292, 2008 | 77 | 2008 |
| Content-driven Music Recommendation: Evolution, State of the Art, and Challenges Y Deldjoo, M Schedl, P Knees arXiv preprint arXiv:2107.11803, 2021 | 71 | 2021 |
| The Quest for Ground Truth in Musical Artist Tagging in the Social Web Era. G Geleijnse, M Schedl, P Knees ISMIR, 525-530, 2007 | 69 | 2007 |
| Multiple Lyrics Alignment: Automatic Retrieval of Song Lyrics. P Knees, M Schedl, G Widmer ISMIR, 564-569, 2005 | 67 | 2005 |
| Exploring music collections in virtual landscapes P Knees, M Schedl, T Pohle, G Widmer IEEE multimedia 14 (3), 46-54, 2007 | 65 | 2007 |
| New paths in music recommender systems research M Schedl, P Knees, F Gouyon Proceedings of the Eleventh ACM Conference on Recommender Systems, 392-393, 2017 | 63 | 2017 |
| A web-based approach to assessing artist similarity using co-occurrences M Schedl, P Knees, G Widmer Proceedings of the Fourth International Workshop on Content-Based Multimedia …, 2005 | 62 | 2005 |
| Music recommendation systems: Techniques, use cases, and challenges M Schedl, P Knees, B McFee, D Bogdanov Recommender systems handbook, 927-971, 2021 | 61 | 2021 |
Markus SchedlProfessor at Johannes Kepler University Linz, Institute of Computational Perceptionjku.at의 이메일 확인됨