Authorship verification as a one-class classification problem
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Journal of the American Society for Information Science and Technology
Foundations and Trends in Information Retrieval
Computational methods in authorship attribution
Journal of the American Society for Information Science and Technology
A survey of modern authorship attribution methods
Journal of the American Society for Information Science and Technology
Fundamentals of Predictive Text Mining
Fundamentals of Predictive Text Mining
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This paper wants to explore quantitative and qualitative practices generally exploited in different scientific fields (philology, mathematics, quantitative linguistics, computer science) in order to reveal forgery. Our study will be conducted on Montale's Diario postumo that shows all the typical features of a suspected forgery. The final aim is to merge all these methods in order to define a taxonomy of annotation elements useful, in this particular context of authorship attribution, for developing a data model to be potentially used in all forgery situations.