skip to main content
10.1145/3264560.3264569acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccbdcConference Proceedingsconference-collections
research-article

Identification of Overpricing in the Purchase of Medication by the Federal Government of Brazil, Using Text Mining and Clustering Based on Ontology

Published:03 August 2018Publication History

ABSTRACT

Increasing the transparency level in his actions and spending is one of the primary duties of the Brazilian Federal Government. The creation of laws that oblige full disclose of all its expenditures through transparency portals enables citizens to supervise all government entities. However, only the dissemination of these data, without a definite standard or the availability of data analysis tools, does not guarantee that the citizen is empowered to play his role. Therefore hence, the objective of this work is to identify overprice in the acquisition of products purchased by the federal government of Brazil using the unstructured data available on the Transparency Portal. The last two-years' worth of purchasing data, available in the Transparency Portal, were extracted, processed and stored. Due to his diverse nature and high volume of data, this study focused only on medicines purchased by the Ministry of Health. Ontology-based text mining and clustering techniques were applied for automatic identification and classification of products. The processing of this information was done through text mining and clustering, based on the ontology registered in another database of the Brazilian government. Because of this work, a consolidated price base per medication was created to allow the identification of distortions in prices practised, facilitating the identification of cases that merit further investigation to unravel fraud to the treasury.

References

  1. ORGANIZAÇÃO DAS NAÇÕES UNIDAS, Corrupção desvia 5% do PIB mundial. 2014. Recovered from https://nacoesunidas.org/onu-corrupcao-desvia-5-do-pib- mundial/. Accessed on February 20th, 2017.Google ScholarGoogle Scholar
  2. MINISTÉRIO PÚBLICO FEDERAL, Operação Lava Jato, 2014. Avaliable in http://lavajato.mpf.mp.br/entenda-o-caso. Accessed on March 19th, 2017.Google ScholarGoogle Scholar
  3. PAIVA E, REVOREDO K, Big Data e Transparência: Utilizando Funções de MapReduce para incrementar a transparência nos gastos públicos. Florianópolis. 2016. XVII Brazilian Symposium on Information Systems. p25--32.Google ScholarGoogle Scholar
  4. ROMMEL C, DE PAIVA E, DA ROCHA H, MENDES G. Methodology for Creating the Brazilian Government Reference Price Database. 2013; Recovered from http://www.lbd.dcc.ufmg.br/colecoes/eniac/2013/0033.pdf. Accessed on February 20th, 2017.Google ScholarGoogle Scholar
  5. PAIVA E, REVOREDO K, Identificação Automática de Produtos e suas Características em Grandes Volumes de Dados Não Estruturados: Uma Proposta para Portais de Transparência Pública. Florianópolis. 2016. XVII Brazilian Symposium on Information Systems. p14--16.Google ScholarGoogle Scholar
  6. BRITO, K. dos S. COSTA, M. A. S, GARCIA, V. MEIRA, S. R. L. Experiences Integrating Heterogeneous Government Open Data Sources to Deliver Services and Promote Transparency in Brazil. Vasteras, Sweden. 2014 IEEE 38th Annual International Computers, Software and Applications Conference. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. ROMMEL C, DE PAIVA E, ROCHA H, MENDES G. Using Clustering and Text Mining to Create a Reference Price Database. 2014; Journal of the Brazilian Society on Computational Intelligence (SBIC), Vol. 12, pp. 38--52, 2014.Google ScholarGoogle Scholar
  8. BASSETI, L. Crawler Transparência. Disponível em https://github.com/LucasBassetti/crawler-transparencia. Acessado em 02/11/2017.Google ScholarGoogle Scholar
  9. CORREA, E. Introdução ao formato JSON. Recovered from: https://www.devmedia.com.br/introducao-ao-formato-json/25275. Accessed on November 6th, 2017.Google ScholarGoogle Scholar

Index Terms

  1. Identification of Overpricing in the Purchase of Medication by the Federal Government of Brazil, Using Text Mining and Clustering Based on Ontology

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        ICCBDC '18: Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing
        August 2018
        98 pages
        ISBN:9781450364744
        DOI:10.1145/3264560

        Copyright © 2018 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 3 August 2018

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed limited

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader