TY  - JOUR
T1  - Big Data, Data Mining, Machine Learning, and Deep Learning Concepts in Crime Data
AU  - Ateş, Emre Cihan
AU  - Bostancı, Gazi Erkan
AU  - Msg, Serdar
PY  - 2020
DA  - November
DO  - 10.26650/JPLC2020-813328
JF  - Ceza Hukuku ve Kriminoloji Dergisi
PB  - İstanbul Üniversitesi
WT  - DergiPark
SN  - 2148-6646
SP  - 293
EP  - 319
VL  - 8
IS  - 2
LA  - en
AB  - Along with the rapid change of information technologies and the widespread use of the internet over time, data stacks with ample diversity and quite large volumes has emerged. The use of data mining is increasing day by day due to the huge part it plays in the acquisition of information by making necessary analyses especially within a large amount of data. Obtaining accurate information is a key factor affecting decision-making processes. Crime data is included among the application areas of data mining, being one of the data stacks which is rapidly growing with each passing day. Crime events constitute unwanted behaviour in every society. For this reason, it is important to extract meaningful information from crime data. This article aims to provide an overview of the use of data mining and machine learning in crime data and to give a new perspective on the decision-making processes by presenting examples of the use of data mining for a crime. For this purpose, some examples of data mining and machine learning in crime and security areas are presented by giving a conceptual framework in the subject of big data, data mining, machine learning, and deep learning along with task types, processes, and methods.
KW  - Crime
KW  - Big data
KW  - Data mining
KW  - Security
KW  - Policing
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UR  - https://doi.org/10.26650/JPLC2020-813328
L1  - https://dergipark.org.tr/tr/download/article-file/1354184
ER  -