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Quantitative Analysis of Crime Incidents in Chicago Using Data Analytics Techniques

Daniel Rivera Ruiz1,*, Alisha Sawant1

Courant Institute of Mathematical Sciences, New York University, 251 Mercer St, New York 10012, USA.

* Corresponding Author: Daniel Rivera Ruiz. Email: .

Computers, Materials & Continua 2019, 59(2), 389-396.


In this paper we aim to identify certain social factors that influence, and thus can be used to predict, the occurrence of crimes. The factors under consideration for this analytic are social demographics such as age, sex, poverty, etc., train ridership, traffic density and the number of business licenses per community area in Chicago, IL. A factor will be considered pertinent if there is high correlation between it and the number of crimes of a particular type in that community area.


Cite This Article

D. Rivera Ruiz and A. Sawant, "Quantitative analysis of crime incidents in chicago using data analytics techniques," Computers, Materials & Continua, vol. 59, no.2, pp. 389–396, 2019.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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