A Supervised Classifier for Police Reports at the State of Pará, Brazil
Resumo
This paper describes the development of a supervised classifier constructed upon knowledge extracted from police report public databases, in the years between 2019 and 2021 in the state of Pará, Brazil. The classifier achieved an accuracy of approximately 78% for the prediction of 463 unique labels related to public safety. The resulting model can be used to improve the statistical processes of criminal analysts, both in quantitative and qualitative terms.Referências
Brasil (2019). O Sinesp. Date of access: March 16, 2022.
Chollet, F. (2018). Deep Learning with Python. Manning Shelter Island, 1st edition.
da Silva Amorim, M. and Pereira, J. R. S. (2019). Tipificação de ocorrências policiais utilizando machine learning. p. 50.
de Castro, U. R. M. (2020). Explorando aprendizagem supervisionada em dados heterogêneos para predição de crimes. p. 85.
de Vargas, W. A. L. (2019). Data science & segurança pública: padrões estatísticos sobre as ocorrências de flagrantes em roubo de celular na cidade de São Paulo. p. 52.
Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1746-1751, Doha, Qatar. Association for Computational Linguistics.
Kshatri, S. S., Singh, D., Narain, B., Bhatia, S., Quasim, M. T., and Sinha, G. R. (2021). An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach. IEEE Access, 9:67488-67500.
Ratul, M. A. R. (2020). A Comparative Study on Crime in Denver City Based on Machine Learning and Data Mining. CoRR, abs/2001.02802.
Chollet, F. (2018). Deep Learning with Python. Manning Shelter Island, 1st edition.
da Silva Amorim, M. and Pereira, J. R. S. (2019). Tipificação de ocorrências policiais utilizando machine learning. p. 50.
de Castro, U. R. M. (2020). Explorando aprendizagem supervisionada em dados heterogêneos para predição de crimes. p. 85.
de Vargas, W. A. L. (2019). Data science & segurança pública: padrões estatísticos sobre as ocorrências de flagrantes em roubo de celular na cidade de São Paulo. p. 52.
Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1746-1751, Doha, Qatar. Association for Computational Linguistics.
Kshatri, S. S., Singh, D., Narain, B., Bhatia, S., Quasim, M. T., and Sinha, G. R. (2021). An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach. IEEE Access, 9:67488-67500.
Ratul, M. A. R. (2020). A Comparative Study on Crime in Denver City Based on Machine Learning and Data Mining. CoRR, abs/2001.02802.
Publicado
16/11/2022
Como Citar
MATOS, Helder; SOUZA, Samara; SANTOS, Reginaldo; COSTA, João Weyl; COSTA, Cleyton.
A Supervised Classifier for Police Reports at the State of Pará, Brazil. In: ESCOLA REGIONAL DE ALTO DESEMPENHO NORTE 2 (ERAD-NO2) E ESCOLA REGIONAL DE APRENDIZADO DE MÁQUINA E INTELIGÊNCIA ARTIFICIAL NORTE 2 (ERAMIA-NO2), 2. , 2022, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 21-24.
DOI: https://doi.org/10.5753/erad-no2.2022.228238.
