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111010

DEVELOPING SPATIO-TEMPORAL DYNAMIC CLUSTERING ALGORITHMS FOR IDENTIFYING CRIME HOT SPOTS IN KUWAIT

Article

Last updated: 26 Dec 2024

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Subjects

-

Tags

Electrical Engineering, Computer Engineering and Electrical power and machines engineering.

Abstract

As crime rates are increasing worldwide, crime mining requires more efficient algorithms that can handle current situations. Identifying crime hot spot areas via clustering spatio-temporal data is an emerging research area. In this paper, dynamic clustering algorithms for spatio-temporal crime data are proposed to detect hot crime spots in Kuwait. Kuwait governorates are taken as case study: the capital, Hawalli, Al-Ahmady, Al-Jahra, Al-Farawaniya, and Mubarak Al-kebeer. In addition, different crime types are considered: act of discharge and humiliation, adultery, aggravated assault, bribery, counter fitting, drugs, embezzlement, fight or resist employee on job, forging of official documents, weapon, robbery and attempted robbery, suicide and attempted suicide, and bank theft. Applying Random subspace classification to those clustered data, 98% accuracy and 99.4% ROC are obtained, having precision (98.7%), recall (98.4%), and F1 (98.28%).

DOI

10.21608/jesaun.2015.111010

Keywords

Spatio-temporal data mining, hot spot detection, intelligent crime mining, random subspace classification, and clustering

Authors

First Name

Taysir H. A.

Last Name

Soliman

MiddleName

-

Affiliation

Information Systems Dept., Faculty of Computers and Information, Assiut University, Egypt

Email

taysser.soliman@fci.au.edu.eg

City

-

Orcid

-

First Name

Khulood

Last Name

Al Ommar

MiddleName

-

Affiliation

Information Systems Dept., Faculty of Computers and Information, Assiut University, Egypt

Email

-

City

-

Orcid

-

First Name

Youssef B.

Last Name

Mahdy

MiddleName

-

Affiliation

Computer Science Dept., Faculty of Computers and Information, Assiut University, Egypt

Email

-

City

-

Orcid

-

Volume

43

Article Issue

No 1

Related Issue

16629

Issue Date

2015-01-01

Receive Date

2014-12-08

Publish Date

2015-01-01

Page Start

1

Page End

15

Print ISSN

1687-0530

Online ISSN

2356-8550

Article File

JESAUN_Volume 43_Issue No 1_Pages 1-15.pdf

PDF . 1.3MB

Link

https://jesaun.journals.ekb.eg/article_111010.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=111010

Order

1

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

DEVELOPING SPATIO-TEMPORAL DYNAMIC CLUSTERING ALGORITHMS FOR IDENTIFYING CRIME HOT SPOTS IN KUWAIT

Details

Type

Article

Created At

23 Jan 2023