Recognizing textual entailment: Models and applications I Dagan, D Roth, F Zanzotto, M Sammons Springer Nature, 2022 | 421 | 2022 |
Viewpoint: Human-in-the-loop Artificial Intelligence FM Zanzotto Journal of Artificial Intelligence Research 64, 243-252, 2019 | 328 | 2019 |
Terminology extraction: an analysis of linguistic and statistical approaches MT Pazienza, M Pennacchiotti, FM Zanzotto Knowledge Mining, 255-279, 2005 | 324 | 2005 |
Estimating linear models for compositional distributional semantics FM Zanzotto, I Korkontzelos, F Fallucchi, S Manandhar Proceedings of the 23rd international conference on computational …, 2010 | 178 | 2010 |
Building the Italian syntactic-semantic treebank S Montemagni, F Barsotti, M Battista, N Calzolari, O Corazzari, A Lenci, ... Treebanks: Building and using parsed corpora, 189-210, 2003 | 175 | 2003 |
Breast cancer prognosis using a machine learning approach P Ferroni, FM Zanzotto, S Riondino, N Scarpato, F Guadagni, M Roselli Cancers 11 (3), 328, 2019 | 136 | 2019 |
A machine learning approach to textual entailment recognition FM Zanzotto, M Pennacchiotti, A Moschitti Natural Language Engineering 15 (4), 551-582, 2009 | 97 | 2009 |
Parsing engineering and empirical robustness R Basili, FM Zanzotto Natural Language Engineering 8 (2-3), 97-120, 2002 | 93 | 2002 |
Automatic learning of textual entailments with cross-pair similarities FM Zanzotto, A Moschitti Proceedings of 44th Annual meeting of the Association for computational …, 2006 | 89 | 2006 |
A contrastive approach to term extraction R Basili, A Moschitti, MT Pazienza, FM Zanzotto Proceedings of the 4th Terminology and Artificial Intelligence Conference …, 2001 | 85 | 2001 |
Risk assessment for venous thromboembolism in chemotherapy-treated ambulatory cancer patients: a machine learning approach P Ferroni, FM Zanzotto, N Scarpato, S Riondino, U Nanni, M Roselli, ... Medical Decision Making 37 (2), 234-242, 2017 | 84 | 2017 |
Linguistic redundancy in twitter FM Zanzotto, M Pennacchiotti, K Tsioutsiouliklis Proceedings of the Conference on Empirical Methods in Natural Language …, 2011 | 76 | 2011 |
Semeval-2013 task 5: Evaluating phrasal semantics I Korkontzelos, T Zesch, FM Zanzotto, C Biemann Second Joint Conference on Lexical and Computational Semantics (* SEM …, 2013 | 67 | 2013 |
Validation of a machine learning approach for venous thromboembolism risk prediction in oncology P Ferroni, FM Zanzotto, N Scarpato, S Riondino, F Guadagni, M Roselli Disease markers 2017 (1), 8781379, 2017 | 64 | 2017 |
Predicting VTE in cancer patients: candidate biomarkers and risk assessment models S Riondino, P Ferroni, FM Zanzotto, M Roselli, F Guadagni Cancers 11 (1), 95, 2019 | 61 | 2019 |
Fast and effective kernels for relational learning from texts A Moschitti, FM Zanzotto Proceedings of the 24th international conference on Machine learning, 649-656, 2007 | 60 | 2007 |
Distributed tree kernels FM Zanzotto, L Dell'Arciprete International Conference on Machine Learning (ICML), 2012 | 56 | 2012 |
KERMIT: Complementing transformer architectures with encoders of explicit syntactic interpretations FM Zanzotto, A Santilli, L Ranaldi, D Onorati, P Tommasino, F Fallucchi Proceedings of the 2020 conference on empirical methods in natural language …, 2020 | 54 | 2020 |
Symbolic, distributed, and distributional representations for natural language processing in the era of deep learning: A survey L Ferrone, FM Zanzotto Frontiers in Robotics and AI 6, 153, 2020 | 54 | 2020 |
Expanding textual entailment corpora fromwikipedia using co-training FM Zanzotto, M Pennacchiotti Proceedings of the 2nd Workshop on The People’s Web Meets NLP …, 2010 | 50 | 2010 |