Fabio Massimo Zanzotto

Qualifica
ASSOCIATO CONFERMATO
Fonte dei dati: Archivio della Ricerca http://art.torvergata.it
  1. Ferroni, P., Zanzotto, F.m., Riondino, S., Scarpato, N., Guadagni, F., & Roselli, M. (2019). Breast Cancer Prognosis Using a Machine Learning Approach. CANCERS, 11(3), 328. Dettagli
  2. Riondino, S., Ferroni, P., Zanzotto, F.m., Roselli, M., & Guadagni, F. (2019). Predicting VTE in cancer patients: Candidate biomarkers and risk assessment models. CANCERS, 11(1), 95. Dettagli
  3. Zanzotto, F.m. (2019). Viewpoint: Human-in-the-loop artificial intelligence. THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 64 - (Computer Science:Artificial Intelligence Q1 http://www.scimagojr.com/journalsearch.php?q=24330&tip=sid&clean=0 ), 243-253. Dettagli
  4. Anastasi, S., Ansaldi, S.m., Augugliaro, G., Biancolini, M.e., Bragatto, P., Cardarilli, G.c., et al. (2018). SMARTBENCH: QUANDO LA SICUREZZA NEGLI STABILIMENTI INDUSTRIALI DIVENTA SMART. A&C. ANALISI E CALCOLO, 86. Dettagli
  5. Ferroni, P., Roselli, M., Zanzotto, F.m., & Guadagni, F. (2018). Artificial intelligence for cancer-associated thrombosis risk assessment. THE LANCET. HAEMATOLOGY, 5(9), e391. Dettagli
  6. Milazzo, M.f., Ansaldi, S.m., Bragatto, P.a., Di Condina, T., & Zanzotto, F.m. (2018). Monitoraggio e gestione dei meccanismi di deterioramento di attrezzature in pressione attraverso un approccio ontologico. In SAFAP 2018. Dettagli
  7. Zanzotto, F.m. (2018). L’Intelligenza Artificiale: dal “grande furto” a una più giusta distribuzione dei profitti. MENABO' DI ETICA ED ECONOMIA. Dettagli
  8. Zanzotto, F.m., & Santilli, A. (2018). SyntNN at SemEval-2018 Task 2: is Syntax Useful for Emoji Prediction? Embedding Syntactic Trees in Multi Layer Perceptrons. In Proceedings of The 12th International Workshop on Semantic Evaluation. Dettagli
  9. Ferroni, P., Zanzotto, F.M., Scarpato, N., Riondino, S., Guadagni, F., & Roselli, M. (2017). Validation of a machine learning approach for venous thromboembolism risk prediction in oncology. DISEASE MARKERS, 2017, 8781379. Dettagli
  10. Guadagni, F., Zanzotto, F.m., Scarpato, N., Rullo, A., Riondino, S., Ferroni, P., et al. (2017). RISK: A random optimization interactive system based on kernel learning for predicting breast cancer disease progression. In 5th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2017 (pp. 189-196). Springer Verlag. Dettagli
  11. Zanzotto, F.m., & Ferrone, L. (2017). Can we explain natural language inference decisions taken with neural networks? Inference rules in distributed representations. In Proceedings of the International Joint Conference on Neural Networks (pp.3680-3687). Institute of Electrical and Electronics Engineers Inc.. Dettagli
  12. Zanzotto, F.m., & Ferrone, L. (2017). Have you lost the thread? Discovering on-going conversations in scattered dialog blocks. ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, 7 - (Computer Science: Human-Computer Interaction Q1 http://www.scimagojr.com/journalsearch.php?q=21100301601&tip=sid&clean=0 )(2). Dettagli
  13. Ferroni, P., Zanzotto, F.m., Scarpato, N., Riondino, S., Nanni, U., Roselli, M., et al. (2016). Risk assessment for venous thromboembolism in chemotherapy treated ambulatory cancer patients: a machine learning approach. MEDICAL DECISION MAKING. Dettagli
  14. Senay, G., Zanzotto, F.M., Ferrone, L., & Rigazio, L. (2015). Predicting Embedded Syntactic Structures from Natural Language Sentences with Neural Network Approaches. In Proceedings of the NIPS Workshop on cognitive computation: integrating neural and symbolic approaches co-located with the 29th Annual conference on neural information processing systems (NIPS 2015). CEUR-WS. Dettagli
  15. Ferrone, L., & Zanzotto, F.M. (2015). Distributed Smoothed Tree Kernel. IJCOL, 1. Dettagli
  16. Ferrone, L., Zanzotto, F.M., & Carreras, X. (2015). Decoding Distributed Tree Structures. In A.a.M. Dediu (a cura di), Statistical Language and Speech Processing (pp. 73-83). Springer International Publishing. Dettagli
  17. Zanzotto, F.m., Ferrone, L., & Baroni, M. (2015). When the whole is not greater than the combination of its parts: A ``decompositional'' look at compositional distributional semantics. COMPUTATIONAL LINGUISTICS, 41 - (Computer Science:Artificial Intelligence Q2 http://www.scimagojr.com/journalsearch.php?q=26801&tip=sid&clean=0 )(1). Dettagli
  18. Caselli, T., Chiari, I., Gangemi, A., Jezek, E., Oltramari, A., Vetere, G., et al. (2014). Senso Comune as a Knowledge Base of Italian language: the Resource and its Development. In Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 & the Fourth International Workshop EVALITA 2014 (pp.93-97). Pisa : Pisa University Press. Dettagli
  19. Ferrone, L., & Zanzotto, F. (2014). Distributed Smoothed Tree Kernel. In Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 & the Fourth International Workshop EVALITA 2014 (pp.169-174). Pisa : Pisa University Press. Dettagli
  20. Ferrone, L., & Zanzotto, F. (2014). haLF: Comparing a Pure CDSM Approach with a Standard Machine Learning System for RTE. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014) (pp.300-304). Dublin, Ireland : Association for Computational Linguistics and Dublin City University. Dettagli
  21. Ferrone, L., & Zanzotto, F.m. (2014). Towards Syntax-aware Compositional Distributional Semantic Models. In Proceedings of international conference on computational linguistics (COLING) (GGS Conference Rating 2 - A) (pp.--). Dettagli
  22. Jezek, E., Vieu, L., Zanzotto, F., Vetere, G., Oltramari, A., Gangemi, A., et al. (2014). Enriching ‘Senso Comune’with Semantic Role Sets. In Proceedings of the 10th Joint ISO-ACL SIGSEM Workshop on Interoperable Semantic Annotation (pp.86-94). Dettagli
  23. Lisi, E., Donati, E., & Zanzotto, F. (2014). Più l’ascolto e più Mi piace! Social media e Radio: uno studio preliminare del successo dei post. In Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 & the Fourth International Workshop EVALITA 2014 (pp.239-243). Pisa : Pisa University Press. Dettagli
  24. Pham, T.N., Ferrone, L., & Zanzotto, F. (2014). Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels. In Proceedings of *Sem 2014 (pp.--). Dettagli
  25. Dagan, I., Roth, D., Sommons, M., & Zanzotto, F.m. (2013). Recognizing Textual Entailment: Models and Applications. San Francisco / Ft. Collins / -- USA : Morgan & Claypool Publishers - ( Computer Science:Computer Networks and Communications Q1 https://www.scimagojr.com/journalsearch.php?q=21100865101&tip=sid&clean=0 ). Dettagli
  26. Ferrone, L., & Zanzotto, F.m. (2013). Linear Compositional Distributional Semantics and Structural Kernels. In Proceedings of the Joint Symposium of Semantic Processing (JSSP) (pp.--). Dettagli
  27. Filice, S., Croce, D., Basili, R., & Zanzotto, F. (2013). Linear Online Learning over Structured Data with Distributed Tree Kernels. In Proceedings of International Conference on Machine Learning Applications (ICMLA) (pp.--). Dettagli
  28. Korkontzelos, I., Zesch, T., Zanzotto, F., & Biemann, C. (2013). SemEval-2013 Task 5: Evaluating Phrasal Semantics. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (pp.--). USA : Association for Computational Linguistics (ACL). Dettagli
  29. Oltramari, A., Vetere, G., Chiari, I., Jezek, E., Zanzotto, F., Nissim, M., et al. (2013). Senso Comune: A Collaborative Knowledge Resource for Italian. In The People's Web Meets NLP: Collaboratively Constructed Language Resources (pp. --). Berlin - : Springer-Verlag Berlin Heidelberg. Dettagli
  30. Sorgente, A., Brancati, N., Giannone, C., Zanzotto, F., Mele, F., & Basili, R. (2013). Chatting to Personalize and Plan Cultural Itineraries. In UMAP 2013 Extended Proceedings (pp.--). Dettagli
  31. Tonna, L., & Zanzotto, F. (2013). Artisti per VideoGioco. Firenze : Le Lettere. Dettagli
  32. Zanzotto, F., & Dell'Arciprete, L. (2013). Transducing Sentences to Syntactic Feature Vectors: an Alternative Way to "Parse"?. In Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality (pp.40-49). Sofia : Association for Computational Linguistics. Dettagli
  33. Chisaroli, F., & Zanzotto, F. (a cura di). (2012). Scritture brevi di oggi. Quaderni di Linguistica Zero. napoli : Università degli studi di Napoli “L’Orientale”. Dettagli
  34. Chiusarli, F., & Zanzotto, F. (a cura di). (2012). Scritture brevi nelle lingue moderne Quaderni di Linguistica Zero. napoli : Università degli studi di Napoli “L’Orientale”. Dettagli
  35. Dell'Arciprete, L., Murphy, B., & Zanzotto, F. (2012). Parallels between Machine and Brain Decoding. In Brain Informatics 2012 (pp. 162-174). BERLIN HEIDELBERG -- DEU : Springer-Verlag. Dettagli
  36. Francesca, F., & Zanzotto, F.M. (2012). Exploiting Transitivity in Probabilistic Models for Ontology Learning. In Semi-Automatic Ontology Development: Processes and Resources (pp. 259-293). IGI Global. Dettagli
  37. Vetere, G., Oltramari, A., Chiari, I., Jezek, E., Vieu, L., & Zanzotto, F. (2012). Senso Comune, an Open Knowledge Base for Italian. REVUE TAL, 53, --. Dettagli
  38. Zanzotto, F. (2012). ChatBot: le macchine chiacchierone. In Comunicazione digitale e comunicazione in rete. Nozioni, competenze, applicazioni (pp. --). Roma : Aracne. Dettagli
  39. Zanzotto, F., & Pennacchiotti, M. (2012). Language Evolution in Social Media: a Preliminary Study. LINGUISTICA ZERO, --. Dettagli
  40. Zanzotto, F., & Tudorache, A. (2012). Travel With Words: An Innovative Vision on Travelling. In Proceedings of the Workshop on Tourism Facilities held jointly with Web Intelligence Conference (pp.107-111). Dettagli
  41. Zanzotto, F., Tsumoto, S., Tsumoto, N., & Yao, Y. (a cura di). (2012). Brain Informatics, International Conference, BI 2012, Macau, China, December 4-7, 2012, Proceedings. BERLIN HEIDELBERG -- DEU : Springer-Verlag. Dettagli
  42. Zanzotto, F.M., Tsumoto, S., Taatgen, N., & Yao, Y. (2012). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface. In F.M. Zanzotto (a cura di), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. V-VII). Springer Verlag. Dettagli
  43. Zanzotto, F.m., & Dell'Arciprete, L. (2012). Distributed Tree Kernels. In Proceedings of International Conference on Machine Learning (ICML) - http://www.scimagojr.com/journalsearch.php?q=21100217201&tip=sid&clean=0 (GGS Conference Rating 1 A++) (pp.--). Dettagli
  44. Prezioso, S., Croce, D., & Zanzotto, F. (2011). Reading what machines “think”: a challenge for nanotechnology. JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 8(10), 2066-2071. Dettagli
  45. Zanzotto, F.m., Pennacchiotti, M., & Tsioutsiouliklis, K. (2011). Linguistic redundancy in Twitter. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) - (GGS Conference Ranking 1 A+) (pp.659-669). edinburgh : Association for Computational Linguistics. Dettagli
  46. Fallucchi, F., & Zanzotto, F.M. (2011). Inductive probabilistic taxonomy learning using singular value decomposition. NATURAL LANGUAGE ENGINEERING, 17 - http://www.scimagojr.com/journalsearch.php?q=28380&tip=sid&clean=0(1), 71-94. Dettagli
  47. Matveeva, I., Màrquez, L., Moschitti, A., & Zanzotto, F.M. (2011). Preface. In ACL HLT 2011 - TextGraphs 2011: Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop. Dettagli
  48. Zanzotto, F.m., Dell'Arciprete, L., & Moschitti, A. (2011). Efficient graph Kernels for textual entailment recognition. FUNDAMENTA INFORMATICAE, 107 - ( Computer Science:Information Systems Q2 http://www.scimagojr.com/journalsearch.php?q=28474&tip=sid&clean=0 )(2-3), 199-222. Dettagli
  49. Zanzotto, F.M., & Croce, D. (2010). Comparing EEG/ERP-like and fMRI-like techniques for reading machine thoughts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.133-144). Dettagli
  50. Banea, C., Moschitti, A., Somasundaran, S., & Zanzotto, F.M. (2010). Introduction. In ACL 2010 - TextGraphs 2010: 2010 Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop (pp.iii-iv). Dettagli
  51. Fallucchi, F., & Zanzotto, F.M. (2010). Transitivity in semantic relation learning. In Proceedings of the 6th IEEE International conference on natural language processing and kwoledge engineering (NLP-KE) (pp.552-559). Dettagli
  52. Fallucchi, F., Pazienza, M.T., & Zanzotto, F.M. (2010). Generic ontology learners on application domains. In Proceedings of the international conference on language resources and evaluation. Dettagli
  53. Mehdad, Y., Moschitti, A., & Zanzotto, F.m. (2010). Syntactic/semantic structures for textual entailment recognition. In Proceedings of Human language technologies: the 2010 annual conference of the North American chapter of the Association for computational linguistics (NAACL) - (GGS Conference Ranking 1 A+) (pp.1020-1028). Dettagli
  54. Zanzotto, F.m., Korkontzelos, I., Fallucchi, F., & Manandhar, S. (2010). Estimating linear models for compositional distributional semantics. In Proceedings of the 23rd international conference on computational linguistics (COLING) (GGS Conference Rating 2 A). Dettagli
  55. Fallucchi, F., & Zanzotto, F.m. (2009). Singular value decomposition for Feature Selection in Taxonomy Learning. In Proceedings of the Conference on Recent Advances on Natural Language Processing. John Benjamins. Dettagli
  56. Fallucchi, F., Scarpato, N., Stellato, A., & Zanzotto, F.m. (2009). Probabilistic Ontology Learner in Semantic Turkey. In R. Serra, & R. Cucchiara (a cura di), AI*IA 2009: Emergent Perspectives in Artificial Intelligence (pp. 294-303). Springer. Dettagli
  57. Zanzotto, F.M., & Croce, D. (2009). Reading what machines "think". In BI 2009: Proceedings of the Brain Informatics Conference - Bejing, China, October 2009 (pp.159-170). Springer-Verlag. Dettagli
  58. Zanzotto, F.M., Pennacchiotti, M., & Moschitti, A. (2009). A Machine learning approach to textual entailment recognition. NATURAL LANGUAGE ENGINEERING, 15 - http://www.scimagojr.com/journalsearch.php?q=28380&tip=sid&clean=0(4), 551-582. Dettagli
  59. Zanzotto, F.m., & Dell'Arciprete, L. (2009). Efficient kernels for sentence pair classification. In Proceedings of the 2009 Conference on Empirical Methods on Natural Language Processing (EMNLP) - http://www.scimagojr.com/journalsearch.php?q=19900195077&tip=sid&clean=0 - (GGS Conference Ranking 1 A+) (pp.91-100). Stroudsburg : Association for Computational Linguistics (ACL). Dettagli
  60. Pennacchiotti, M., & Zanzotto, F.m. (2008). Natural Language Processing across time: an empirical investigation on Italian. In Advances in Natural Language Processing, 6th International Conference, GoTAL 2008, Gothenburg, Sweden, August 25-27,2008, Proceedings (pp.371-382). Springer. Dettagli
  61. Moschitti, A., & Zanzotto, F.m. (2007). Fast and effective kernels for relational learning from texts. In Proceedings of 24th annual International Conference on Machine Learning (ICML) - http://www.scimagojr.com/journalsearch.php?q=21100217201&tip=sid&clean=0 (GGS Conference Rating 1 A++) (pp.649-656). ACM. Dettagli
  62. Pennacchiotti, M., & Zanzotto, F.m. (2007). Learning shallow semantic rules for textual entailment. In International Conference Recent Advances in Natural Language Processing, RANLP (pp.458-462). Association for Computational Linguistics (ACL). Dettagli
  63. Zanzotto, F.M. (2007). Lost in grammar translation. INTELLIGENZA ARTIFICIALE, 4(2). Dettagli
  64. Zanzotto, F.m., & Moschitti, A. (2007). Experimenting a "general purpose" textual entailment learner in AVE. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.510-517). Dettagli
  65. Pazienza, M.t., Pennacchiotti, M., & Zanzotto, F.m. (2006). Discovering verb relations in corpora: Distributional versus non-distributional approaches. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.1042-1052). Springer Verlag. Dettagli
  66. Pazienza, M.t., Pennacchiotti, M., & Zanzotto, F.m. (2006). Learning textual entailment on a distance feature space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.240-260). Springer Verlag. Dettagli
  67. Zanzotto, F.M., Moschitti, A., Pennacchiotti, M., & Pazienza, M.T. (2006). Learning textual entailment from examples. In The Second PASCAL recognizing textual entailment challenge: proceedings of the challenges workshop / Bernardo Magnini, Ido Dagan (editors) (pp.50). PASCAL. Dettagli
  68. Zanzotto, F.m., & Moschitti, A. (2006). Automatic learning of textual entailments with cross-pair similarities. In Proceedings of 44th Annual meeting of the Association for computational linguistics (ACL) - (GGS Conference Rating 1 A++) (pp.401-408). Morristown (NJ, USA) : Association for Computational Linguistics. Dettagli
  69. Zanzotto, F.m., Pennacchiotti, M., & Pazienza, M.t. (2006). Discovering asymmetric entailment relations between verbs using selectional preferences. In Proceedings of 44th Annual meeting of the Association for computational linguistics (ACL) - (GGS Conference Rating 1 A++) (pp.849-856). Morristown (NJ, USA) : Association for Computational Linguistics. Dettagli
  70. Pazienza, M.T., Stellato, A., Henriksen, L., Paggio, P., & Zanzotto, F.M. (2005). Ontology mapping to support multilingual ontology-based question answering. In Poster and Demo Proceedings of the 4th International Semantic Web Conference (ISWC-2015). Dettagli
  71. Pazienza, M.T., Pennacchiotti, M., & Zanzotto, F.M. (2005). Terminology extraction: an analysis of linguistic and statistical approaches. In S. Sirmakessis (a cura di), Knowledge mining: proceedings of the NEMIS 2004 final conference (pp. 255-279). Berlin : Springer. Dettagli
  72. Pazienza, M.t., Pennacchiotti, M., & Zanzotto, F.m. (2005). A linguistic inspection of textual entailment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 315-326). Springer Verlag. Dettagli
  73. Pazienza, M.t., Pennacchiotti, M., Vindigni, M., & Zanzotto, F.m. (2005). AI/NLP technologies applied to spacecraft mission design. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 239-248). Springer Verlag. Dettagli
  74. Atzeni, P., Basili, R., Hansen, D.h., Missier, P., Paggio, P., Pazienza, M.t., et al. (2004). Ontology-based question answering in a Federation of University Sites: The MOSES case study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.413-420). Dettagli
  75. Paggio, P., Hansen, D., Basili, R., Pazienza, M.T., & Zanzotto, F.M. (2004). Ontology-based question analysis in a multilingual environment: the MOSES case study. In Proceedings of the Workshop OntoLex 2004. Dettagli
  76. Roberto, B., Michele, V., & Fabio Massimo Zanzotto, (2004). Understanding the Web through its Language. In ACM/IEEE/WIC Web Intelligence - http://www.scimagojr.com/journalsearch.php?q=145091&tip=sid&clean=0 (pp.736-739). Dettagli
  77. Basili, R., Moschitti, A., Pazienza, M.t., & Zanzotto, F.m. (2003). Personalizing Web Publishing via Information Extraction. IEEE INTELLIGENT SYSTEMS, 18 - (Computer Science: Artificial Intelligence Q1 http://www.scimagojr.com/journalsearch.php?q=110111&tip=sid&clean=0 ), 62-70. Dettagli
  78. Basili, R., Vindigni, M., & Zanzotto, F.M. (2003). Integrating ontological and linguistic knowledge for Conceptual Information Extraction. In Proceedings of IEEE/WIC Web Intelligence (WI 2003) (GSS Conference Rating CORE:B, LiveSHINE:A, MA:B). Dettagli
  79. MONTEMAGNI, S., BARSOTTI, F., BATTISTA, M., CALZOLARI, N., CORAZZARI, O., ZAMPOLLI, A., et al. (2003). The Italian Syntactic-Semantic Treebank: Architecture, Annotation, Tools and Evaluation. LINGUISTICA COMPUTAZIONALE, 16-18. Dettagli
  80. Montemagni, S., Barsotti, F., Battista, M., Calzolari, N., Corazzari, O., Lenci, A., et al. (2003). Building the Italian Syntactic-Semantic Treebank. In A. Abeillé (a cura di), Treebanks: Building and Using Parsed Corpora (pp. 189-210). Springer Netherlands. Dettagli
  81. Basili R, & Zanzotto, F.M. (2002). Parsing engineering and empirical robustness. NATURAL LANGUAGE ENGINEERING, 8 - http://www.scimagojr.com/journalsearch.php?q=28380&tip=sid&clean=0, 97-120. Dettagli
  82. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2002). Acquisition of conceptual domain dictionaries via decision tree learning. In Proceedings of 15th European Conference on Artificial Intelligence (ECAI 2002) (pp.480-484). IOS Press. Dettagli
  83. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2002). Decision trees as explicit domain term definition. In Proceedings of 19th International Conference on Computational Linguistic (COLING2002). MORRISTOWN, NJ -- USA : Association for Computational Linguistics. Dettagli
  84. Moschitti, A., & Zanzotto, F.M. (2002). A robust summarization system to explain document categorization. In Proceedings of 2nd Workshop of Robust Methods in Analysis of Natural language Data (ROMAND). Dettagli
  85. BASILI, R., CATIZONE, R., PADRÓ, L., PAZIENZA, M., RIGAU, G., SETZER, A., et al. (2001). Multilingual Authoring: the NAMIC approach. In Proceedings of the EACL/ACL Workshop on Human Language Technology and Knowledge Management (HLT & KM). Dettagli
  86. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2001). Flexible Parsing Architectures for NLP Applications. In Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence. LONDON -- GBR : Springer-Verlag. Dettagli
  87. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2001). Modelling the syntactic contextual information for term extraction. In Proceedings of the Conference on Recent Advances in Natural Language Processing RANLP2001. Dettagli
  88. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2001). Web-based information access: Multilingual Automatic Authoring. In PROCEEDINGS OF THE Third IEEE Conference on Information Technology: Coding and Computing ITCC-2002. Dettagli
  89. BASILI, R., PAZIENZA, M.T., MOSCHITTI, A., & ZANZOTTO, F.M. (2001). A Contrastive Approach to Term Extraction. In Proceedings of the 4th Terminology and Artificial Intelligence Conference. Dettagli
  90. BARSOTTI, F., BASILI, R., BATTISTA, M., CALZOLARI, N., CORAZZARI, O., MONTE, R.D., et al. (2000). The Italian Syntactic-Semantic Treebank: Architecture, Annotation, Tools and Evaluation. In A. Abeillé (a cura di), Treebanks: building and using parsed corpora (pp. 189-210). DORDRECHT : Kluwer. Dettagli
  91. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (2000). Customizable Modular Lexicalized Parsing. In PROCEEDINGS OF THE 6TH INTERNATIONAL WORKSHOP ON PARSING TECHNOLOGY. Dettagli
  92. BASILI, R., PAZIENZA, M.T., VINDIGNI, M., & ZANZOTTO, F.M. (2000). Tuning lexicons to new operational scenarios. In Proceedings of the Second International Conference on Language Resources and Evaluation Conference (LREC2000). Dettagli
  93. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (1999). Lexicalizing a shallow parser. In PROCEEDINGS OF TALN99 CONFERENCE, LE TRAITMENT AUTOMATIQUE DES LANGUES NATURELLES. Dettagli
  94. BASILI, R., PAZIENZA, M.T., VINDIGNI, M., & ZANZOTTO, F.M. (1999). Adaptive parsing for time-constrained tasks. In Proceedings of AIIA99 workshop on "Natural Language Processing and Speech Recognition". Dettagli
  95. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (1998). Efficient Parsing for Information Extraction. In Procedings of the European Conference on Artificial Intelligence. Dettagli
  96. BASILI, R., PAZIENZA, M.T., & ZANZOTTO, F.M. (1998). Evaluating a Parsing System for Italian. In Proceedings of the Workshop on The Evaluation of Parsing System, held with the International Conference on Language Resources and Evaluation. Dettagli