Title: Discovery of rare association rules in the distribution of lawsuits in the federal justice system of Southern Brazil

Authors: Lúcia Adriana Dos Santos Gruginskie; Guilherme Luís Roehe Vaccaro; Leonardo Dagnino Chiwiacowsky; Attila Elod Blesz Jr.

Addresses: Graduate Program in Production Engineering and Systems, Unisinos, Sao Leopoldo RS, Brazil ' Graduate Program in Production Engineering and Systems, Unisinos, Sao Leopoldo RS, Brazil ' Program in Industrial Engineering, UCS-Universidade de Caxias do Sul, Bento Gonçalves City, RS, Brazil ' Graduate Program in Production Engineering and Systems, Unisinos, Sao Leopoldo RS, Brazil

Abstract: In the context of data mining, infrequent association rules may be beneficial for analysing rare or extreme cases with very low support values and high confidence. In researching risky situations or allocating specific resources, such rules may have a much greater impact than rules with high support value. The objective of this study is to obtain association rules from the database of lawsuits filed in the Federal Court of Southern Brazil in 2016, including both frequent and rare rules. By finding these rules, especially rare ones, the information collected can assist in the decision-making process, in this case, such as training clerks or establishing specialised courts.

Keywords: association rules; rare rules; distribution of lawsuits; Brazilian federal justice; data mining.

DOI: 10.1504/IJBIDM.2019.10015160

International Journal of Business Intelligence and Data Mining, 2021 Vol.18 No.2, pp.127 - 154

Received: 15 Jan 2018
Accepted: 10 Jun 2018

Published online: 28 Jan 2021 *

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