@conference {266,
	title = {L{\textquoteright}Epistola a Cangrande al vaglio della Computational Authorship Verification: risultati preliminari (con una postilla sulla cosiddetta {\textquotedblleft}XIV Epistola di Dante Alighieri{\textquotedblright})},
	booktitle = {Nuove inchieste sull{\textquoteright}epistola a Cangrande: atti della giornata di studi, Pisa 18 dicembre 2018},
	year = {2020},
	publisher = {Pisa University Press},
	organization = {Pisa University Press},
	abstract = {In this work we apply techniques from computational Authorship Verification (AV) to the problem of detecting whether the {\textquotedblleft}Epistle to Cangrande{\textquotedblright} is an authentic work by Dante Alighieri or is instead the work of a forger. The AV algorithm we use is based on {\textquotedblleft}machine learning{\textquotedblright}: the algorithm {\textquotedblleft}trains{\textquotedblright} an automatic system (a {\textquotedblleft}classifier{\textquotedblright}) to detect whether a certain Latin text is Dante{\textquoteright}s or not Dante{\textquoteright}s, by exposing it to a corpus of example Latin texts by Dante and example Latin texts by authors coeval to Dante. The detection is based on the analysis of a  set of stylometric features, i.e., style-related linguistic traits whose us-age frequencies tend to represent an author{\textquoteright}s unconscious {\textquotedblleft}signature{\textquotedblright}. 
The analysis carried out in this work suggests that, of the two parts into which the Epistle is traditionally subdivided, neither is Dante{\textquoteright}s. Experiments in which we have applied our AV system to each text in the corpus  suggest that the system has a fairly high degree of accuracy, thus lending credibility to its hypothesis about the authorship of the Epistle. In the last  section of this paper we apply our system to what has been hypothesized to be {\textquotedblleft}Dante{\textquoteright}s 14th Epistle{\textquotedblright}; the system rejects, with very high confidence, the hypothesis that this epistle might be Dante{\textquoteright}s.},
	isbn = {978-88-3339-333-9},
	author = {Silvia Corbara and Alejandro Moreo and Fabrizio Sebastiani and Mirko Tavoni},
	editor = {Alberto Casadei}
}
@conference {265,
	title = {The Epistle to Cangrande Through the Lens of Computational Authorship Verification},
	booktitle = {New Trends in Image Analysis and Processing {\textendash} ICIAP 2019},
	year = {2019},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The Epistle to Cangrande is one of the most controversial among the works of Italian poet Dante Alighieri. For more than a hundred years now, scholars have been debating over its real paternity, i.e., whether it should be considered a true work by Dante or a forgery by an unnamed author. In this work we address this philological problem through the methodologies of (supervised) Computational Authorship Verification, by training a classifier that predicts whether a given work is by Dante Alighieri or not. We discuss the system we have set up for this endeavour, the training set we have assembled, the experimental results we have obtained, and some issues that this work leaves open.},
	isbn = {978-3-030-30754-7},
	doi = {https://doi.org/10.1007/978-3-030-30754-7_15},
	author = {Silvia Corbara and Moreo, Alejandro and Sebastiani, Fabrizio and Tavoni, Mirko},
	editor = {Cristani, Marco and Prati, Andrea and Lanz, Oswald and Messelodi, Stefano and Sebe, Nicu}
}
