Multi Clustering Technique in Data Mining for Crime Scene Investigation

Carlos D. Correa, Chih-Hsing Chu

Abstract


The retrieval of the informative knowledge is quite interesting, from the huge data and it is also a challenging task. Data mining is the powerful technology to analyse the data skilfully from different perspectives and summarizes it  to useful  information. The  finding of  the cold  spot and  hot spot  is the  challenging task  in crime analysis. Crime is the act that harms the public, increases the violence, demolishes the assets and denies the respect to people. A major challenge facing all law-enforcement and intelligence-gathering organizations is accurately and efficiently analyzing the growing volumes of crime data. Another major challenge faced by the Nigerian law enforcement agencies is the lack of a central repository where all data collections concerning crimes and criminals are stored which possess a bigger problem, as there are many cases of data repetition, and as such it is difficult for law enforcers to see patterns in crimes during analysis. So In this paper crime analysis is done by  performing  clustering  on  crime  dataset  using rapid miner tool. 


Keywords


Crime Scene Analysis, High Dimensional Data Clustering.

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References


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