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Fabio Massimo Zanzotto
Fabio Massimo Zanzotto
Associate Professor, University of Rome "Tor Vergata"
Bestätigte E-Mail-Adresse bei uniroma2.it - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Recognizing textual entailment: Models and applications
I Dagan, D Roth, F Zanzotto, M Sammons
Springer Nature, 2022
4062022
Terminology extraction: an analysis of linguistic and statistical approaches
MT Pazienza, M Pennacchiotti, FM Zanzotto
Knowledge Mining, 255-279, 2005
3152005
Viewpoint: Human-in-the-loop Artificial Intelligence
FM Zanzotto
Journal of Artificial Intelligence Research 64, 243-252, 2019
2642019
Estimating linear models for compositional distributional semantics
FM Zanzotto, I Korkontzelos, F Fallucchi, S Manandhar
Proceedings of the 23rd international conference on computational …, 2010
1752010
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
1742003
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
1222019
A machine learning approach to textual entailment recognition
FM Zanzotto, M Pennacchiotti, A Moschitti
Natural Language Engineering 15 (4), 551-582, 2009
962009
Parsing engineering and empirical robustness
R Basili, FM Zanzotto
Natural Language Engineering 8 (2-3), 97-120, 2002
952002
Automatic learning of textual entailments with cross-pair similarities
FM Zanzotto, A Moschitti
Proceedings of 44th Annual meeting of the Association for computational …, 2006
892006
A contrastive approach to term extraction
R Basili, A Moschitti, MT Pazienza, FM Zanzotto
Proceedings of the 4th Terminology and Artificial Intelligence Conference …, 2001
832001
Linguistic redundancy in twitter
FM Zanzotto, M Pennacchiotti, K Tsioutsiouliklis
Proceedings of the Conference on Empirical Methods in Natural Language …, 2011
752011
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
722017
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
632013
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
602007
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
542019
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, 2017
542017
Distributed tree kernels
FM Zanzotto, L Dell'Arciprete
International Conference on Machine Learning (ICML), 2012
532012
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
502010
Discovering asymmetric entailment relations between verbs using selectional preferences
FM Zanzotto, M Pennacchiotti, MT Pazienza
Proceedings of 44th Annual meeting of the Association for computational …, 2006
482006
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
472020
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