Classification of Brazilian Supreme Federal Court Documents: A Comparative Study

被引：0

作者：

Martins, Victor ^{[1
]}

Silva, Cleison ^{[2
]}

机构：

[1] PPCA UFPA, Tucuri, Brazil

[2] PPCA UFPA, Turucui, Brazil

来源：

2024 6TH INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING, ICNLP 2024 | 2024年

关键词：

Machine Learning; Natural Language Processing; Document Classification; Law;

D O I：

10.1109/ICNLP60986.2024.10692383

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper evaluates the application of Artificial Intelligence algorithms for the legal document classification. Algorithms are divided into linear classifiers SVM and Logistic Regression, ULMFiT Language Model and HAN. The studied dataset is called VICTOR, composed of documents from the Brazilian Supreme Federal Court (STF). The article concludes that all machine learning algorithms tested can be applied to classify legal documents from the employed dataset. Additionally, despite being less complex, the TF-IDF together linear classifiers outperform the experimented Language Model and HAN in terms of F1-score.

引用

页码：1 / 5

页数：5

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