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

Datos Bibliográficos

ID12972304
AutoresAlice Cavalieri (0000-0003-0553-8574), Pietro Ducange (0000-0003-4510-1350, Ospedale San Pietro Fatebenefratelli, autor de correspondencia), Sarah Fabi (0000-0001-7149-7147), Federico Russo (0000-0002-0052-6796, Twitter (United States)), Nicola Tonellotto (0000-0002-7427-1001, Twitter (United States))
Año2022
Volumen20
Número3
Páginas213-234
Fecha de publicación2022-06-09
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaJournal of Information Technology & Politics (JOURNAL)
Identificadores de la revistaISSN: 1933-169X • E-ISSN: 1933-1681
EditorialRoutledge (PUBLISHER • GB)
DOI10.1080/19331681.2022.2082622
OpenAlexW4281658826
IdiomaEN
Citas recibidas1
Referencias citadas45

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

Categorization · Chamber of Deputies · Information retrieval · Natural language processing · Political science · Politics · Task (project management · Text categorization · Work (physics · Advanced Text Analysis Techniques · Computational and Text Analysis Methods · Computer Science · Engineering · Topic Modeling · Artificial Intelligence

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Obras citantes distintas1
Citas por año1
Intervalo de citas2025 - 2025 (1)
Velocidad de citaciónrecent
Altamente citadoNo
Tipos de citaNeutras: 1
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae