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Authors: Vanessa Ribeiro 1 ; Jeanne Louize Emygdio 1 ; Guilherme Paiva 1 ; Bruno Praciano 1 ; Valério Martins 1 ; Edna Canedo 1 ; 2 ; Fábio Mendonça 1 ; Rafael Timóteo de Sousa Júnior 1 and Ricardo Puttini 1

Affiliations: 1 National Science and Technology Institute on Cyber Security, Electrical Engineering Department, University of Brasília (UnB), P.O. Box 4466, Brasília DF, Brazil ; 2 Department of Computer Science, University of Brasília (UnB), P.O. Box 4466, Brasília DF, Brazil

Keyword(s): Natural Language Processing, Artificial Intelligence, Public Administration Agency, Jurisprudence, Antitrust.

Abstract: Natural Language Processing (NLP) and Machine Learning (ML) resources can be used in Jurisprudence to deal more accurately with the large volume of documents and data in this context to provide speed to the execution of processes and greater accuracy to judicial decisions. This article aims to present applied research with a qualitative approach and exploratory objective, technically characterized as a case study. The research was conducted in a Brazilian federal public administration agency to verify the existence of antitrust practices in the pharmaceutical field and the monitoring of such practices by the institution. To this end, a methodological path was established based on three stages: building the corpus, running the NLP pipeline and consultation of the results in the Jurisprudence Search System (BJ System). In compliance with the objective of the case study, it was possible to identify the performance of the agency around the domain elicited, as well as indications of the e xistence of antitrust practices, since the 276 documents retrieved from the BJ system relate directly to routine processes executed by the agency, either in the sense of investigation, trial or analysis of the business practices. (More)

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Paper citation in several formats:
Ribeiro, V.; Louize Emygdio, J.; Paiva, G.; Praciano, B.; Martins, V.; Canedo, E.; Mendonça, F.; Timóteo de Sousa Júnior, R. and Puttini, R. (2023). Natural Language Processing Applied in the Context of Economic Defense: A Case Study in a Brazilian Federal Public Administration Agency. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-648-4; ISSN 2184-4992, SciTePress, pages 630-637. DOI: 10.5220/0011991900003467

@conference{iceis23,
author={Vanessa Ribeiro. and Jeanne {Louize Emygdio}. and Guilherme Paiva. and Bruno Praciano. and Valério Martins. and Edna Canedo. and Fábio Mendon\c{C}a. and Rafael {Timóteo de Sousa Júnior}. and Ricardo Puttini.},
title={Natural Language Processing Applied in the Context of Economic Defense: A Case Study in a Brazilian Federal Public Administration Agency},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2023},
pages={630-637},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011991900003467},
isbn={978-989-758-648-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Natural Language Processing Applied in the Context of Economic Defense: A Case Study in a Brazilian Federal Public Administration Agency
SN - 978-989-758-648-4
IS - 2184-4992
AU - Ribeiro, V.
AU - Louize Emygdio, J.
AU - Paiva, G.
AU - Praciano, B.
AU - Martins, V.
AU - Canedo, E.
AU - Mendonça, F.
AU - Timóteo de Sousa Júnior, R.
AU - Puttini, R.
PY - 2023
SP - 630
EP - 637
DO - 10.5220/0011991900003467
PB - SciTePress