Analytical Model of Recommendations for the Mitigation of Theft Risks

Juan Camilo Montaña; Enrique Gonzalez

doi:10.1007/978-3-031-19951-6_3

Analytical Model of Recommendations for the Mitigation of Theft Risks

Juan Camilo Montaña
, Enrique Gonzalez

Department of Systems Engineering

Universidad Javeriana

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Crime rates around the world are constantly increasing, and the crime of theft is one of those that most affects the population. This type of crime has occurrences and patterns in certain places and periods. This article presents an analytical model that allows generating recommendations to mitigate the risk of being a victim of this crime. The model is responsible for preprocessing the data, performing fuzzy partitioning, generating frequent patterns, and creating fuzzy association rules to generate recommendations. The model was applied to the case study associated with the area with the highest theft crimes rate in Bogotá.

Original language	English
Title of host publication	Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers
Editors	Enrique Gonzalez, Mariela Curiel, Andrés Moreno, Angela Carrillo-Ramos, Rafael Páez, Leonardo Flórez-Valencia
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	31-45
Number of pages	15
ISBN (Print)	9783031199509
DOIs	https://doi.org/10.1007/978-3-031-19951-6_3
State	Published - 2022
Event	15th Colombian Congress on Advances in Computing, CCC 2021 - Bogota, Colombia Duration: 22 Nov 2021 → 26 Nov 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1594 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	15th Colombian Congress on Advances in Computing, CCC 2021
Country/Territory	Colombia
City	Bogota
Period	22/11/21 → 26/11/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Association rules
Fuzzy partitioning
Recommendations model
Theft risk

Access to Document

10.1007/978-3-031-19951-6_3

Cite this

Montaña, J. C., & Gonzalez, E. (2022). Analytical Model of Recommendations for the Mitigation of Theft Risks. In E. Gonzalez, M. Curiel, A. Moreno, A. Carrillo-Ramos, R. Páez, & L. Flórez-Valencia (Eds.), Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers (pp. 31-45). (Communications in Computer and Information Science; Vol. 1594 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-19951-6_3

Montaña, Juan Camilo ; Gonzalez, Enrique. / Analytical Model of Recommendations for the Mitigation of Theft Risks. Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers. editor / Enrique Gonzalez ; Mariela Curiel ; Andrés Moreno ; Angela Carrillo-Ramos ; Rafael Páez ; Leonardo Flórez-Valencia. Springer Science and Business Media Deutschland GmbH, 2022. pp. 31-45 (Communications in Computer and Information Science).

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abstract = "Crime rates around the world are constantly increasing, and the crime of theft is one of those that most affects the population. This type of crime has occurrences and patterns in certain places and periods. This article presents an analytical model that allows generating recommendations to mitigate the risk of being a victim of this crime. The model is responsible for preprocessing the data, performing fuzzy partitioning, generating frequent patterns, and creating fuzzy association rules to generate recommendations. The model was applied to the case study associated with the area with the highest theft crimes rate in Bogot{\'a}.",

keywords = "Association rules, Fuzzy partitioning, Recommendations model, Theft risk",

author = "Monta{\~n}a, \{Juan Camilo\} and Enrique Gonzalez",

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editor = "Enrique Gonzalez and Mariela Curiel and Andr{\'e}s Moreno and Angela Carrillo-Ramos and Rafael P{\'a}ez and Leonardo Fl{\'o}rez-Valencia",

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Montaña, JC & Gonzalez, E 2022, Analytical Model of Recommendations for the Mitigation of Theft Risks. in E Gonzalez, M Curiel, A Moreno, A Carrillo-Ramos, R Páez & L Flórez-Valencia (eds), Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers. Communications in Computer and Information Science, vol. 1594 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 31-45, 15th Colombian Congress on Advances in Computing, CCC 2021, Bogota, Colombia, 22/11/21. https://doi.org/10.1007/978-3-031-19951-6_3

Analytical Model of Recommendations for the Mitigation of Theft Risks. / Montaña, Juan Camilo; Gonzalez, Enrique.
Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers. ed. / Enrique Gonzalez; Mariela Curiel; Andrés Moreno; Angela Carrillo-Ramos; Rafael Páez; Leonardo Flórez-Valencia. Springer Science and Business Media Deutschland GmbH, 2022. p. 31-45 (Communications in Computer and Information Science; Vol. 1594 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gonzalez, Enrique

PY - 2022

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N2 - Crime rates around the world are constantly increasing, and the crime of theft is one of those that most affects the population. This type of crime has occurrences and patterns in certain places and periods. This article presents an analytical model that allows generating recommendations to mitigate the risk of being a victim of this crime. The model is responsible for preprocessing the data, performing fuzzy partitioning, generating frequent patterns, and creating fuzzy association rules to generate recommendations. The model was applied to the case study associated with the area with the highest theft crimes rate in Bogotá.

AB - Crime rates around the world are constantly increasing, and the crime of theft is one of those that most affects the population. This type of crime has occurrences and patterns in certain places and periods. This article presents an analytical model that allows generating recommendations to mitigate the risk of being a victim of this crime. The model is responsible for preprocessing the data, performing fuzzy partitioning, generating frequent patterns, and creating fuzzy association rules to generate recommendations. The model was applied to the case study associated with the area with the highest theft crimes rate in Bogotá.

KW - Association rules

KW - Fuzzy partitioning

KW - Recommendations model

KW - Theft risk

UR - https://www.scopus.com/pages/publications/85142679888

U2 - 10.1007/978-3-031-19951-6_3

DO - 10.1007/978-3-031-19951-6_3

M3 - Conference contribution

AN - SCOPUS:85142679888

SN - 9783031199509

T3 - Communications in Computer and Information Science

SP - 31

EP - 45

BT - Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers

A2 - Gonzalez, Enrique

A2 - Curiel, Mariela

A2 - Moreno, Andrés

A2 - Carrillo-Ramos, Angela

A2 - Páez, Rafael

A2 - Flórez-Valencia, Leonardo

PB - Springer Science and Business Media Deutschland GmbH

T2 - 15th Colombian Congress on Advances in Computing, CCC 2021

Y2 - 22 November 2021 through 26 November 2021

ER -

Montaña JC, Gonzalez E. Analytical Model of Recommendations for the Mitigation of Theft Risks. In Gonzalez E, Curiel M, Moreno A, Carrillo-Ramos A, Páez R, Flórez-Valencia L, editors, Advances in Computing - 15th Colombian Congress, CCC 2021, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 31-45. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-19951-6_3

Analytical Model of Recommendations for the Mitigation of Theft Risks

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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