Title: General crime from the data mining point of view. A systematic literature review

Authors: Maria Antonia Walteros-Alcázar; Nicolas Aguirre-Yacup; Sandra Patricia Castillo-Landínez; Pablo Eduardo Caicedo-Rodríguez

Addresses: Engineering Faculty, Corporación Universitaria Autónoma del Cauca, Calle 5, 3-85, 190003503, Popayán, Cauca, Colombia ' Engineering Faculty, Corporación Universitaria Autónoma del Cauca, Calle 5, 3-85, 190003503, Popayán, Cauca, Colombia ' Engineering Faculty, Corporación Universitaria Autónoma del Cauca, Calle 5, 3-85, 190003503, Popayán, Cauca, Colombia ' Engineering Faculty, Corporación Universitaria Autónoma del Cauca, Calle 5, 3-85, 190003503, Popayán, Cauca, Colombia

Abstract: In recent decades, crime has become an issue of great concern to nations, which is why there is significant progress in the development of investigations in different areas. The literature review considers the data mining techniques applied to crime research, throughout the analysis of four thematic axes: countries, data sources, data mining techniques and software employed in different articles. The analysis used a systematic methodology to examine the 111 articles selected among 2008-2018 from almost 70 journals. The articles of this review are focused on different types of crime. The findings indicated that the USA is the most active country analysing crimes using data mining techniques; also, the most common sources are open data websites and crime studies. Studies based on general crime types are more frequent than those covering a specific type of crime, the algorithm mainly used in the studies is clustering and the most used software is WEKA.

Keywords: data mining; DM; crime; criminal patterns; law enforcement; data mining techniques; algorithms; review; knowledge discovery; literature review; LR.

DOI: 10.1504/IJBIDM.2021.118186

International Journal of Business Intelligence and Data Mining, 2021 Vol.19 No.3, pp.371 - 393

Received: 30 Apr 2019
Accepted: 22 Oct 2019

Published online: 29 Sep 2021 *

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