A REVIEW OF DETECTION OF CRIME USING DATA CLASSIFICATION
Keywords:
Crime information report, statistics data analysisAbstract
When crimes occur regularly in a society, they will have an impact on the institutions and organizations there. Because of this, it is important to investigate the causes of crime, as well as the variables and relationships that contribute to its occurrence, in order to discover the best methods for managing crime and preventing its spread. The major purpose of this research is to categorize clustered crimes according to their recurrence frequency throughout various years. Many types of criminal activity are analyzed, investigated, and pattern-discovered via data mining. To an actual crime dataset collected by the police in England and Wales between 1990 and 2011, we used a theoretical model based on data mining methods like clustering and classification. To enhance the quality of the model and get rid of aspects that weren't adding anything to it, we gave each one a weight. Outlier Detection operator settings are optimized using the RapidMiner software and the Genetic Algorithm (GA).
References
MINGCHEN FENG , JIANGBIN ZHENG, JINCHANG REN , (Senior Member, IEEE), AMIR HUSSAIN , (Senior Member, IEEE), XIUXIU LI, YUE XI , AND QIAOYUAN LIU on Big Data Analytics and Mining for Effective Visualization and Trends Forecasting of Crime Data Received May 8, 2019, accepted July 9, 2019, date of publication July 22, 2019 Digital Object Identifier 10.1109/ACCESS.2019.2930410. [2] Deepika K.K, Smitha Vinod on “Crime analysis in India using data mining techniques” INTERNATIONAL JOURNAL OF ENGINEEEING & TECHNOLOGY
. International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-4, Issue-5, May.-
J. Han, and M. Kamber, ―Data mining: concepts and techniques,‖ 2nd Edition, Morgan Kaufmann Publisher, 2001.
S. Joshi, and B. Nigam, ―Categorizing the document using multi class classification in data mining,‖ International Conference on Computational Intelligence and Communication Systems, 2011.
T. Phyu, ―Survey of classification techniques in data mining,‖ Proceedings of the International Multi Conference of Engineers and Computer Scientists Vol. IIMECS 2009, March 18 - 20, 2009, Hong Kong.
S.B. Kim, H.C. Rim, D.S. Yook, and H.S. Lim, ―Effective Methods for Improving Naïve Bayes Text Classifiers,‖ In Proceeding of the 7th Pacific Rim International Conference on Artificial Intelligence, Vol.2417, 2002.
S. Sindhiya, and S. Gunasundari, ―A survey on Genetic algorithm based feature selection for disease diagnosis system,‖ IEEE International Conference on Computer Communication and Systems(ICCCS), Feb 20- 21, 2014, Chermai, INDIA.
P. Gera, and R. Vohra, ―Predicting Future Trends in City Crime Using Linear Regression,‖ IJCSMS (International Journal of Computer Science & Management Studies) Vol. 14, Issue 07Publishing Month: July 2014.
L. Ding et al., ―PerpSearch: an integrated crime detection system,‖ 2009 IEEE 161-163 ISI 2009, June 8-11, 2009, Richardson, TX, USA.
K. Bogahawatte, and S. Adikari, ―Intelligent criminal identification system,‖ IEEE 2013 The 8th International Conference on Computer Science & Education (ICCSE 2013) April 26-28, 2013. Colombo, Sri Lanka.
A. Babakura, N. Sulaiman, and M. Yusuf, ―Improved method of calssification algorithms for crime prediction,‖ International Symposium on Biometrics and Security Technologies (ISBAST) IEEE 2014. [15] S. Sathyadevan, and S. Gangadharan, ―Crime analysis and prediction using data mining,‖ IEEE 2014.
