Assessment of text clustering approaches for legal documents

  • Ingrid L. A. da Silva UFRPE
  • Rafael Ferreira Mello UFRPE
  • Péricles B. C. Miranda UFRPE
  • André C. A. Nascimento UFRPE
  • Isabel W. S. Maldonado NESS Law
  • José L. M. Coelho Filho NESS Law

Resumo


O sistema judiciário é composto por inúmeros documentos relacionados a processos jurídicos. Esses documentos podem conter informações relevantes que suportem a tomada de decisão em processos futuros. No entanto, a coleta dessas informações não é uma tarefa trivial. Este artigo propõe o uso de agrupamento para reunir processos semelhantes e facilitar a coleta de informações. Dessa forma, diferentes abordagens foram avaliadas com a intenção de identificar a mais adequada para realizar esta tarefa. As abordagens foram aplicadas a uma base de dados composta por 1515 textos de fatos de petições iniciais. Essas abordagens foram avaliadas levando em consideração métricas de avaliação internas e os textos dos processos agrupados. Os resultados apontaram que a melhor abordagem para realizar o agrupamento de processos jurídicos é composta pelo algoritmo K-Means e pela técnica de representação TF-IDF em combinação com a técnica PCA.

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Publicado
29/11/2021
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SILVA, Ingrid L. A. da; MELLO, Rafael Ferreira; MIRANDA, Péricles B. C.; NASCIMENTO, André C. A.; MALDONADO, Isabel W. S.; COELHO FILHO, José L. M.. Assessment of text clustering approaches for legal documents. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 37-48. DOI: https://doi.org/10.5753/eniac.2021.18239.

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