| Multilabel classification via calibrated label ranking J Fürnkranz, E Hüllermeier, E Loza Mencía, K Brinker Machine Learning 73 (2), 133-153, 2008 | 766 | 2008 |
| Large-scale Multi-label Text Classification—Revisiting Neural Networks J Nam, J Kim, E Loza Mencía, I Gurevych, J Fürnkranz Machine Learning and Knowledge Discovery in Databases, 437-452, 2014 | 302 | 2014 |
| Efficient pairwise multilabel classification for large-scale problems in the legal domain E Loza Mencia, J Fürnkranz Proceedings of the European Conference on Machine Learning and Principles …, 2008 | 149* | 2008 |
| Deepred–rule extraction from deep neural networks JR Zilke, EL Mencía, F Janssen International Conference on Discovery Science, 457-473, 2016 | 107 | 2016 |
| Maximizing subset accuracy with recurrent neural networks in multi-label classification J Nam, E Loza Mencía, HJ Kim, J Fürnkranz Advances in neural information processing systems 30, 5413-5423, 2017 | 85 | 2017 |
| Efficient voting prediction for pairwise multilabel classification EL Mencía, SH Park, J Fürnkranz Neurocomputing 73 (7-9), 1164-1176, 2010 | 75 | 2010 |
| Pairwise learning of multilabel classifications with perceptrons E Loza Mencia, J Furnkranz Proceedings of the 2008 IEEE International Joint Conference on Neural …, 2008 | 73* | 2008 |
| Pairwise learning of multilabel classifications with perceptrons E Loza Mencia, J Fürnkranz Technical Report TUD–KE–2007–05, 2007 | 73* | 2007 |
| Efficient multilabel classification algorithms for large-scale problems in the legal domain E Loza Mencia, J Fürnkranz Semantic Processing of Legal Texts -- Where the Language of Law Meets the …, 2010 | 69* | 2010 |
| An evaluation of efficient multilabel classification algorithms for large-scale problems in the legal domain E Loza Mencia, J Fürnkranz LWA 2007 Lernen–Wissen–Adaption, 126, 2007 | 69* | 2007 |
| A Hybrid Multi-Strategy Recommender System Using Linked Open Data P Ristoski, E Loza Mencia, H Paulheim | 51 | 2014 |
| All-in text: Learning document, label, and word representations jointly J Nam, EL Mencía, J Fürnkranz Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 38 | 2016 |
| Learning rules for multi-label classification: a stacking and a separate-and-conquer approach EL Mencía, F Janssen Machine Learning 105 (1), 77-126, 2016 | 26 | 2016 |
| Medical concept embeddings via labeled background corpora EL Mencia, G De Melo, J Nam Proceedings of the Tenth International Conference on Language Resources and …, 2016 | 18 | 2016 |
| Which Scores to Predict in Sentence Regression for Text Summarization? M Zopf, EL Mencía, J Fürnkranz Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 16 | 2018 |
| A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets A Schulz, EL Mencía, B Schmidt Information Systems 57, 88-110, 2016 | 15 | 2016 |
| Using semantic similarity for multi-label zero-shot classification of text documents SP Veeranna, J Nam, EL Mencıa, J Fürnkranz Proceeding of European Symposium on Artificial Neural Networks …, 2016 | 15 | 2016 |
| On the combination of two decompositive multi-label classification methods G Tsoumakas, EL Mencıa, I Katakis, SH Park, J Fürnkranz Workshop on Preference Learning, ECML PKDD 9, 114-133, 2009 | 14 | 2009 |
| Segmentation of legal documents E Loza Mencía Proceedings of the 12th International Conference on Artificial Intelligence …, 2009 | 14 | 2009 |
| Beyond centrality and structural features: Learning information importance for text summarization M Zopf, EL Mencía, J Fürnkranz Proceedings of The 20th SIGNLL Conference on Computational Natural Language …, 2016 | 13 | 2016 |
Johannes FürnkranzJohannes Kepler University, LinzVerified email at faw.jku.at
