Clustering of Brazilian legal judgments about failures in air transport service: an evaluation of different approaches

Isabela Cristina Sabo; Thiago Raulino Dal Pont; Pablo Ernesto Vigneaux WiltonAires Jose RoverJomi Fred Huebner

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Clustering of Brazilian legal judgments about failures in air transport service: an evaluation of different approaches

机译：Clustering of Brazilian legal judgments about failures in air transport service: an evaluation of different approaches

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The paper presents different clustering approaches in legal judgments from the Special Civil Court located at the Federal University of Santa Catarina (JEC/UFSC). The subject is Consumer Law, specifically cases in which consumers claim moral and material compensation from airlines for service failures. To identify patterns from the dataset, we apply four types of clustering algorithms: Hierarchical and Lingo (soft clustering), K-means and Affinity Propagation (hard clustering). We evaluate the results based on the following criteria: (1) entropy and purity; (2) algorithm's ability in providing labels; (3) legal expert's evaluation; and (4) experimental complexity. The results demonstrate that the most advantageous approach is Hierarchical Clustering, since it has the best entropy and purity numbers, as well as the least difficulty for the expert to analyze the clusters, and the least experimental complexity. The main contribution of the paper is to show the advantages and disadvantages of each approach, especially to identify labels in unstructured and non-indexed legal texts.

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《Artificial intelligence and law》 |2022年第1期|21-57|共37页
作者
Isabela Cristina Sabo; Thiago Raulino Dal Pont; Pablo Ernesto Vigneaux WiltonAires Jose RoverJomi Fred Huebner;
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作者单位

Department of Law, Federal University of Santa Catarina, Florianopolis, Brazil;

Department of Knowledge Engineering and Management, Federal University of Santa Catarina,Florian6polis, Brazil;

Department of Law and Department of Knowledge Engineering and Management, Federal University of Santa Catarina, Florianopolis, BrazilDepartment of Automation and Systems, Federal University of Santa Catarina, Florianopolis,Brazil;

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正文语种英语
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Consumer law; Air transport service; Unsupervised learning; Hierarchical Clustering; K-means; Lingo; Affinity Propagation;

Clustering of Brazilian legal judgments about failures in air transport service: an evaluation of different approaches

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