A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Surviving the Legal Jungle: Text Classification of Italian Laws in Extremely Noisy Conditions
2020
Italian Conference on Computational Linguistics
In this paper, we present a method based on Linear Discriminant Analysis for legal text classification of extremely noisy data, such as duplicated documents classified in different classes. The results show that Linear Discriminant Analysis obtains very good performances both in clean and noisy conditions, if used as classifier in ensemble learning and in multi-label text classification. Motivation and Background We address text categorization of businessoriented legal documents in Italian, but
dblp:conf/clic-it/ColtrinariAC20
fatcat:4lni6n24cbegzkynvg5hhi4tq4