Roberto Basili | "Tor Vergata" University of Rome (original) (raw)
Papers by Roberto Basili
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts.... more Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts. Many approaches in literature are based on resources that model the prior polarity of words or multi-word expressions, i.e. a polarity lexicon. Such resources are defined by teams of annotators, i.e. a manual annotation is provided to associate emotional or sentiment facets to the lexicon entries. The development of such lexicons is an expensive and language dependent process, making them often not covering all the linguistic sentiment phenomena. Moreover, once a lexicon is defined it can hardly be adopted in a different language or even a different domain. In this paper, we present several Distributional Polarity Lexicons (DPLs), i.e. large-scale polarity lexicons acquired with an unsupervised methodology based on Distributional Models of Lexical Semantics. Given a set of heuristically annotated sentences from Twitter, we transfer the sentiment information from sentences to words. The ...
Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017, 2017
Italian Journal of Computational Linguistics, 2019
Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017
International Journal on Document Analysis and Recognition (IJDAR), 2010
Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition - DeepLA '05, 2005
COLING-02 on SEMANET building and using semantic networks -, 2002
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011
Proceedings of the 15th conference on Computational linguistics -, 1994
Lecture Notes in Computer Science, 2013
Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing - FeatureEng '05, 2005
Lecture Notes in Computer Science, 2009
Natural Language Engineering, 2002
Robustness has been traditionally stressed as a general desirable property of any computational m... more Robustness has been traditionally stressed as a general desirable property of any computational model and system. The human NL interpretation device exhibits this property as the ability to deal with odd sentences. However, the difficulties in a theoretical explanation of robustness within the linguistic modelling suggested the adoption of an empirical notion. In this paper, we propose an empirical definition of robustness based on the notion of performance. Furthermore, a framework for controlling the parser robustness in the design phase is presented. The control is achieved via the adoption of two principles: the modularisation, typical of the software engineering practice, and the availability of domain adaptable components. The methodology has been adopted for the production of CHAOS, a pool of syntactic modules, which has been used in real applications. This pool of modules enables a large validation of the notion of empirical robustness, on the one side, and of the design met...
Computational Linguistics, 2008
The availability of large scale data sets of manually annotated predicate-argument structures has... more The availability of large scale data sets of manually annotated predicate-argument structures has recently favored the use of machine learning approaches to the design of automated semantic role labeling (SRL) systems. The main research in this area relates to the design choices for feature representation and for effective decompositions of the task in different learning models. Regarding the former choice, structural properties of full syntactic parses are largely employed as they represent ways to encode different principles suggested by the linking theory between syntax and semantics. The latter choice relates to several learning schemes over global views of the parses. For example, re-ranking stages operating over alternative predicate-argument sequences of the same sentence have shown to be very effective. In this article, we propose several kernel functions to model parse tree properties in kernel-based machines, for example, perceptrons or support vector machines. In particul...
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Proceedings of the First Italian Conference on Computational Linguistics CLiC-it 2014 and of the Fourth International Workshop EVALITA 2014 9-11 December 2014, Pisa, 2014
Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts.... more Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts. Many approaches in literature are based on resources that model the prior polarity of words or multi-word expressions, i.e. a polarity lexicon. Such resources are defined by teams of annotators, i.e. a manual annotation is provided to associate emotional or sentiment facets to the lexicon entries. The development of such lexicons is an expensive and language dependent process, making them often not covering all the linguistic sentiment phenomena. Moreover, once a lexicon is defined it can hardly be adopted in a different language or even a different domain. In this paper, we present several Distributional Polarity Lexicons (DPLs), i.e. large-scale polarity lexicons acquired with an unsupervised methodology based on Distributional Models of Lexical Semantics. Given a set of heuristically annotated sentences from Twitter, we transfer the sentiment information from sentences to words. The ...
Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017, 2017
Italian Journal of Computational Linguistics, 2019
Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017
International Journal on Document Analysis and Recognition (IJDAR), 2010
Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition - DeepLA '05, 2005
COLING-02 on SEMANET building and using semantic networks -, 2002
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011
Proceedings of the 15th conference on Computational linguistics -, 1994
Lecture Notes in Computer Science, 2013
Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing - FeatureEng '05, 2005
Lecture Notes in Computer Science, 2009
Natural Language Engineering, 2002
Robustness has been traditionally stressed as a general desirable property of any computational m... more Robustness has been traditionally stressed as a general desirable property of any computational model and system. The human NL interpretation device exhibits this property as the ability to deal with odd sentences. However, the difficulties in a theoretical explanation of robustness within the linguistic modelling suggested the adoption of an empirical notion. In this paper, we propose an empirical definition of robustness based on the notion of performance. Furthermore, a framework for controlling the parser robustness in the design phase is presented. The control is achieved via the adoption of two principles: the modularisation, typical of the software engineering practice, and the availability of domain adaptable components. The methodology has been adopted for the production of CHAOS, a pool of syntactic modules, which has been used in real applications. This pool of modules enables a large validation of the notion of empirical robustness, on the one side, and of the design met...
Computational Linguistics, 2008
The availability of large scale data sets of manually annotated predicate-argument structures has... more The availability of large scale data sets of manually annotated predicate-argument structures has recently favored the use of machine learning approaches to the design of automated semantic role labeling (SRL) systems. The main research in this area relates to the design choices for feature representation and for effective decompositions of the task in different learning models. Regarding the former choice, structural properties of full syntactic parses are largely employed as they represent ways to encode different principles suggested by the linking theory between syntax and semantics. The latter choice relates to several learning schemes over global views of the parses. For example, re-ranking stages operating over alternative predicate-argument sequences of the same sentence have shown to be very effective. In this article, we propose several kernel functions to model parse tree properties in kernel-based machines, for example, perceptrons or support vector machines. In particul...