Sakarya University Journal of Computer and Information Sciences

Yazarlar: İbrahim ÇİL, Sümeyye Gizem ÇAKAR, Nazan SARI, Olcay EYDEMİR

Konular:Bilgisayar Bilimleri, Disiplinler Arası Uygulamalar

DOI:10.35377/saucis.02.03.648342

Anahtar Kelimeler:Biclustering Method,CC Algorithm,Xmotif Algorithm,Crime Data,Data Mining

Özet: In terms of safety of the social life, it is very important to foresee the crimes and take the necessary precautions before the crime is committed. For this purpose, crime analysis should be carried out in order for security units to take necessary measures. In this regard, the data mining approach makes a significant contribution to the security units in the analysis of large data. In this context, different data analysis methods are used to estimate and identify potential crime areas. By using dual clustering methods in the detection of crime zones, clustering of crime areas and crime types at the same time provides more comprehensive results than traditional clustering methods. In this study, CC and Xmotif algorithms were used on the data set of “Crimes in Boston” to determine the crime sites by using data mining approach. The results were obtained by using R-project 3.5.3 software. It was found that CC algorithm gives better results for this data set than Xmotif algorithm.

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