| Freesound Datasets: A Platform for the Creation of Open Audio Datasets. E Fonseca, J Pons, X Favory, F Font, D Bogdanov, A Ferraro, S Oramas, ... ISMIR, 486-493, 2017 | 291 | 2017 |
| Sound and music recommendation with knowledge graphs S Oramas, VC Ostuni, TD Noia, X Serra, ED Sciascio ACM Transactions on Intelligent Systems and Technology (TIST) 8 (2), 1-21, 2016 | 189 | 2016 |
| Multi-label music genre classification from audio, text, and images using deep features S Oramas, O Nieto, F Barbieri, X Serra arXiv preprint arXiv:1707.04916, 2017 | 181 | 2017 |
| Multimodal deep learning for music genre classification S Oramas, F Barbieri, O Nieto Caballero, X Serra Ubiquity Press, 2018 | 177 | 2018 |
| A deep multimodal approach for cold-start music recommendation S Oramas, O Nieto, M Sordo, X Serra Proceedings of the 2nd workshop on deep learning for recommender systems, 32-37, 2017 | 130 | 2017 |
| SemEval-2018 task 9: Hypernym discovery J Camacho-Collados, CD Bovi, LE Anke, S Oramas, T Pasini, E Santus, ... Proceedings of the 12th international workshop on semantic evaluation, 712-724, 2018 | 128 | 2018 |
| Multimodal metric learning for tag-based music retrieval M Won, S Oramas, O Nieto, F Gouyon, X Serra ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 57 | 2021 |
| Information extraction for knowledge base construction in the music domain S Oramas, L Espinosa-Anke, M Sordo, H Saggion, X Serra Data & Knowledge Engineering 106, 70-83, 2016 | 49 | 2016 |
| Supervised and unsupervised learning of audio representations for music understanding MC McCallum, F Korzeniowski, S Oramas, F Gouyon, AF Ehmann arXiv preprint arXiv:2210.03799, 2022 | 45 | 2022 |
| Exploring customer reviews for music genre classification and evolutionary studies S Oramas, L Espinosa-Anke, A Lawlor | 40 | 2016 |
| A Semantic-Based Approach for Artist Similarity. S Oramas, M Sordo, LE Anke, X Serra ISMIR, 100-106, 2015 | 35 | 2015 |
| The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale. D Bogdanov, A Porter, H Schreiber, J Urbano, S Oramas ISMIR, 360-367, 2019 | 33 | 2019 |
| ELMD: An automatically generated entity linking gold standard dataset in the music domain S Oramas, LE Anke, M Sordo, H Saggion, X Serra Proceedings of the Tenth International Conference on Language Resources and …, 2016 | 33 | 2016 |
| Natural language processing for music knowledge discovery S Oramas, L Espinosa-Anke, F Gómez, X Serra Journal of New Music Research 47 (4), 365-382, 2018 | 22 | 2018 |
| Tracking Melodic Patterns in Flamenco Singing by Analyzing Polyphonic Music Recordings. A Pikrakis, F Gómez, S Oramas, JM Díaz-Báñez, J Mora, ... ISMIR, 421-426, 2012 | 20 | 2012 |
| Artist similarity with graph neural networks F Korzeniowski, S Oramas, F Gouyon arXiv preprint arXiv:2107.14541, 2021 | 18 | 2021 |
| Mood classification using listening data F Korzeniowski, O Nieto, M McCallum, M Won, S Oramas, E Schmidt arXiv preprint arXiv:2010.11512, 2020 | 17 | 2020 |
| FlaBase: Towards the Creation of a Flamenco Music Knowledge Base. S Oramas, F Gómez, E Gómez, J Mora ISMIR, 378-384, 2015 | 15 | 2015 |
| A rule-based approach to extracting relations from music tidbits S Oramas, M Sordo, L Espinosa-Anke Proceedings of the 24th International Conference on World Wide Web, 661-666, 2015 | 14 | 2015 |
| Open knowledge extraction challenge 2017 R Speck, M Röder, S Oramas, L Espinosa-Anke, AC Ngonga Ngomo Semantic Web Challenges: 4th SemWebEval Challenge at ESWC 2017, Portoroz …, 2017 | 13 | 2017 |
Xavier SerraDepartment of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), BarcelonaZweryfikowany adres z upf.edu