Abstract
In this paper we present some results obtained in humour classification over a corpus of Italian quotations manually extracted and tagged from the Wikiquote project. The experiments were carried out using both a multinomial Naïve Bayes classifier and a Support Vector Machine (SVM). The considered features range from single words to n-grams and sentence length. The obtained results show that it is possible to identify the funny quotes even with the simplest features (bag of words); the bayesian classifier performed better than the SVM. However, the size of the corpus size is too small to support definitive assertions.
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Buscaldi, D., Rosso, P. (2007). Some Experiments in Humour Recognition Using the Italian Wikiquote Collection. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_58
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DOI: https://doi.org/10.1007/978-3-540-73400-0_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73399-7
Online ISBN: 978-3-540-73400-0
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