A Descriptive and Predictive Analysis Tool for Criminal Data: A Case Study from Brazil

被引：0

作者：

Andrade, Yan ^{[1
]}

Pimenta, Matheus ^{[3
]}

Amarante, Gabriel ^{[3
]}

Faria, Antonio Hot ^{[2
,3
]}

Vilas-Boas, Marcelo ^{[2
]}

da Silva, Joao Paulo ^{[2
]}

Rocha, Felipe ^{[2
]}

da Silva, Jamicel ^{[2
]}

Meira Jr, Wagner ^{[3
]}

Teodoro, George ^{[3
]}

Rocha, Leonardo ^{[1
]}

Ferreira, Renato ^{[3
]}

机构：

[1] Univ Fed Sao Joao del Rei, Sao Joao Del Rei, Brazil

[2] Policia Mil Minas Gerais, Belo Horizonte, MG, Brazil

[3] Univ Fed Minas Gerais, Belo Horizonte, MG, Brazil

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS-ICCSA 2024, PT II | 2024年 / 14814卷

关键词：

D O I：

10.1007/978-3-031-64608-9_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Addressing the challenge of crime is crucial for governing bodies, requiring informed strategies. This article examines the underutilization of detailed criminal data, collaborating with the Military Police of Minas Gerais, Brazil. We propose a new methodology, materialized in a tool, that is able to transform raw data into strategic information for public security decision-making. The tool evaluation unfolds in three phases: characterizing the data, a descriptive analysis of a real case study, and a predictive analysis. This work highlights the untapped potential in detailed criminal data, emphasizing the pivotal role of precise analysis in deciphering complex dynamics. Collaborating with law enforcement aims to bridge the gap between data abundance and actionable insights for effective public security strategies.

引用

页码：151 / 169

页数：19

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