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Conference Paper Design and Performance Evaluation of Crime Type and Crime Risk Score Estimation Technique for Fast and Efficient Response of Severe Crimes
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Authors
Myung-Sun Baek, Yong Tae Lee, Kwangho Jang, Heejo Lee, Wonjoo Park
Issue Date
2020-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.1826-1828
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289426
Abstract
In this paper, the machine learning-based estimation technique of crime types and crime risk score is introduced. For development of the estimation technique, the system platform of the introduced technique is also implemented. To predict the crime risk score, crime risk score equation is designed based on the crime severity and degree of damage, and numerical crime risk score is applied to each criminal case. For the crime types and crime risk score estimation, virtual police security data is considered. The data form is the same as the KICS data form. Using the proposed technique and implemented system platform, police can obtain efficient information in the first stage of criminal case reception.
KSP Keywords
Estimation Technique, First stage, Learning-based, Performance evaluation, Risk score, Score estimation, machine Learning, security data