An Intelligent system for the categorization of question time official documents of the Italian Chamber of Deputies

Abstract

ABSTRACT In this work, we present an intelligent system for the automatic categorization of political documents, specifically the documents containing the parliamentary questions collected during the weekly Question Times at the Chamber of Deputies of the Italian Republic. The proposed intelligent system leverages text classification models to perform the document categorization. The system is aimed at supporting and facilitating the research activities of political science scholars, who deal with comparative and longitudinal analysis of thousands of documents. To select the best classification models for our specific task, several classical machine learning and deep learning-based text classification models have been experimentally compared.