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Crime analysis has importance for the detection of crime regions, the prediction of
crimes before processing and the security forces to take necessary measures. By using
biclustering methods to detect crime regions, simultaneous clustering of the types of crimes and
regions where crime is committed to producing more comprehensive results than traditional
clustering methods. In this study, CC and Xmotif algorithms of biclustering methods were
applied to the real data set in order to detect the crime regions. “Crimes in Boston” data set was
used in real data set application. In order to measure the efficiency of the biclusters, the
performance of the algorithms was compared with Chia and Karuturi bicluster score (CCPS).
The results were obtained by using Matlab functions and it was observed that results of the CC
algorithm were better compared to Xmotif algorithm.
International Data Science & Engineering Symposium
IDSES
Nazan SARI
Sümeyye Gizem ÇAKAR
Olcay EYDEMİR
İbrahim ÇİL