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Authors: Leonardo R. De Carvalho 1 ; Felipe S. Lopes 1 ; Jefferson Chaves 1 ; Marcos C. Lima 2 ; Flávio E. Gomes De Deus 3 ; Aletéia P. F. A. von Paungarthem 1 and Flavio De Barros Vidal 1

Affiliations: 1 Department of Computer Science, University of Brasilia, Brasilia, DF, Brazil ; 2 Department of Federal Police, Brasilia, DF, Brazil ; 3 Department of Electrical Engineering, University of Brasilia, Brasilia, DF, Brazil

Keyword(s): Machine Learning, High Performance Computing, Government of Brazil, Official Gazette.

Abstract: Brazil publishes region information, public tenders for the hire of civil servants, and also government contracts with companies in its Official Gazettes. All this volume of information can contain interesting relationships that reveal unique characteristics of the government, such as the effectiveness of public policies and even the existence of illegal schemes. Establishing these relationships is not a trivial task and requires great effort. Therefore, this work proposes the Deep Vacuity platform, which, by using a High-Performance Computing architecture along with Machine Learning techniques, can collect, depurate, consolidate and analyze the data, offering a friendly interface for decision-makers.

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Paper citation in several formats:
R. De Carvalho, L.; Lopes, F.; Chaves, J.; Lima, M.; Gomes De Deus, F.; von Paungarthem, A. and Vidal, F. (2022). Deep-vacuity: A Proposal of a Machine Learning Platform based on High-performance Computing Architecture for Insights on Government of Brazil Official Gazettes. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST, ISBN 978-989-758-613-2; ISSN 2184-3252, pages 136-143. DOI: 10.5220/0011532500003318

@conference{webist22,
author={Leonardo {R. De Carvalho}. and Felipe S. Lopes. and Jefferson Chaves. and Marcos C. Lima. and Flávio E. {Gomes De Deus}. and Aletéia P. F. A. {von Paungarthem}. and Flavio De Barros Vidal.},
title={Deep-vacuity: A Proposal of a Machine Learning Platform based on High-performance Computing Architecture for Insights on Government of Brazil Official Gazettes},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST,},
year={2022},
pages={136-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011532500003318},
isbn={978-989-758-613-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST,
TI - Deep-vacuity: A Proposal of a Machine Learning Platform based on High-performance Computing Architecture for Insights on Government of Brazil Official Gazettes
SN - 978-989-758-613-2
IS - 2184-3252
AU - R. De Carvalho, L.
AU - Lopes, F.
AU - Chaves, J.
AU - Lima, M.
AU - Gomes De Deus, F.
AU - von Paungarthem, A.
AU - Vidal, F.
PY - 2022
SP - 136
EP - 143
DO - 10.5220/0011532500003318