Aplicação da inteligência artificial, ontologia e mineração de dados para classificação de sentenças judiciais
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2021-12-20
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Universidade Federal de Goiás
Resumo
The objective of this work is to apply together ontology with bag-of-words models, similarity
learning, and document classification in texts with uttered decisions. The objective is to
improve the results of data mining in a database of court decisions. An automatic method of
searching sentences in judicial processes related to the one under judgment is developed
using the frequency term-inverse of frequency in documents model together with the Jaccard
similarity coefficient, establishing weights on the co-occurrence of terms in legal texts of the
same category. A dataset with document vectorization is used for supervised training of
machine learning algorithms, aiming to classify new justice processes. The proposed
methodology provides flexibility to the Judiciary, simulating the role of legal advisors in
preparing court decisions with less time and efficiency in the search for jurisprudential
standards. The results obtained show that, through accuracy metrics, the proposed model is
effective and efficient, and can be applied in the process of identification of court decisions.
Thus, the application of artificial intelligence, ontology, and data mining is indicated for
information retrieval in court decisions.
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Citação
CASTRO JUNIOR, A. P. Aplicação da inteligência artificial, ontologia e mineração de dados para classificação de sentenças judiciais. 2021. 170 f. Tese (Doutorado em Engenharia Elétrica e da Computação) - Universidade Federal de Goiás, Goiânia, 2021.