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Editor-in-chief

 
Faculty of Science, University of Brunei Darussalam, Brunei Darussalam   
" It is a great honor to serve as the editor-in-chief of IJIEE. I'll work together with the editorial team. Hopefully, IJIEE will be recognized among the readers in the related field."
IJIEE 2017 Vol.7(3): 99-102 ISSN: 2010-3719
DOI: 10.18178/IJIEE.2017.7.3.669

Crime Analysis Based on Association Rules Using Apriori Algorithm

Mehmet Sevri, Hacer Karacan, and M. Ali Akcayol
Abstract—Data mining is an important technique used in many fields with the purpose of acquiring valuable information from big data. This study aims to reveal the relations between the attributes of independent criminal records. The NIBRS database, which includes criminal records in USA that are recorded in 2013, is used in this study. The association rules created by the Apriori algorithm have been used to extract the relationships between features of criminal records. The experimental results show that the association rules created by the Apriori algorithm are useful for criminal analysis. This study reveals the relationships between the attributes of different criminal records and allows the authorities to establish relationships between new and old incidents.

Index Terms—Crime analysis, assocition rules, apriori, offender profiling.

M. Sevri is with the Informatics Institute, Gazi University Ankara, Turkey (e-mail: mehmetsevri@gazi.edu.tr).
H. Karacan and M. A. Akcayol are with the Computer Engineering Department, Gazi University, Ankara, Turkey (e-mail: hkaracan@gazi.edu.tr, akcayol@gazi.edu.tr).

[PDF]

Cite:Mehmet Sevri, Hacer Karacan, and M. Ali Akcayol, "Crime Analysis Based on Association Rules Using Apriori Algorithm," International Journal of Information and Electronics Engineering vol. 7, no. 3, pp. 99-102, 2017.

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