Offenders Clustering Using Fcm and K-means

Volume 15, Issue 4, pp 294-301 http://dx.doi.org/10.22436/jmcs.015.04.06

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Authors

Sara Farzai - Adib High Education Institute of Mazandaran, Sari, Iran Davood Ghasemi - Shomal University, Amol, Iran Seyed Saeed Mirpour Marzuni

Abstract

One of the most applicable and successful methods to provide security in society is to use data mining techniques to recognize patterns of crimes. Data mining is a field that discovers hidden patterns of large amount of data in large data bases, and also extracts useful knowledge in every field which uses it. Clustering is a technique of data mining that divides data points into many groups so that the members of each group have the most similarity and the members from different groups have the least similarity. In this paper we cluster 100 offenders according to crime they have committed, using Fuzzy C-Means and K-Means algorithms in Matlab and Weka environments. Then we studied the intersections in efficient elements in crime occurrence in each cluster. We obtained interesting results coincided our real data. Hence we have created a pattern which is able to detect crime with considering other attributes, and reversely. It is clear that these detections can help to decrease the effects of crime. Note that Fuzzy C-Means algorithm has provided more accurate results in comparison with K-Means algorithm, because of considering fuzzy point of view and natural uncertainty in the real world.

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Keywords

• Crime
• Offender
• Data Mining
• Clustering.

MSC

•  60E05
•  62H30

References

• [1] A. Corapcıoglu, S. Erdogan , A Cross-Sectional Study on Expression of Anger and Factors Associated With Criminal Recidivism in Prisoners with Prior Offences, Forensic Science International, 140 (2004), 167-1746.
  • View Article
  • Google Scholar


• [2] W. Chung, H. Ch. Chen, W. Chang, SH. Chou , Fighting Cybercrime: A Review and the Taiwan Experience, Decision Support Systems, 41 (2006), 669 - 682.
  • View Article
  • Google Scholar


• [3] D. Karlis, L. Meligkotsidou , Finite Mixtures of Multivariate Poisson Distributions with Application, Journal of Statistical Planning and Inference, 137 (2007), 1942 – 1960.
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [4] J. I. Khan, S. S. Shaikh , Computing in Social Networks With Relationship Algebra, Journal of Network and Computer Applications, 31 (2008), 862–878.
  • View Article
  • Google Scholar


• [5] Sh. T. Li, SH. CH. Kuo, F. CH. Tsai , An Intelligent Decision-Support Model Using FSOM and Rule Extraction for Crime Prevention, Expert Systems with Applications, 37 (2010), 7108–7119.
  • View Article
  • Google Scholar


• [6] H. Liu, E. Brown Donald , Criminal Incident Prediction Using a Point- Pattern-Based Density Model, International Journal of Forecasting, 19 (2003), 603–622.
  • View Article
  • Google Scholar


• [7] B. Moon, J. B. McCluskey, C. P. McCluskey , General Theory of Crime and Computer Crime: An Empirical Test, Journal of Criminal Justice, 38 (2010), 767–772.
  • View Article
  • Google Scholar


• [8] G. C. Oatley, B. W. Ewart , Crimes Analysis Software: ‘Pins in Maps’, Clustering and Bayes Net Prediction, Expert Systems with Applications, 25 (2003), 569–588.
  • View Article
  • Google Scholar


• [9] M. Sanoroyan , Neural Symptoms Norm in Men Prisoners, Notion and behavior, No. 4 (2005)


• [10] L. A. Zadeh , Fuzzy sets, Information and Control, 8(3) (1965), 338–353.


• [11] P. Dadsetan, Criminal psychology, Samt publication, Tehran (2006)


• [12] A. Sayyah , Universal Arabic-Farsi dictionary, 1st edition. , ()


• [13] M. Keynia , Criminal psychology, 1st edition, Roshd publication (2005)


• [14] , Iranian Human Rights, (Islamic criminal law), (2004)