ABSTRACT
Spatio-temporal data mining techniques are used for crime analysis for their knowledge oriented and meaningful visual representation of crime incidents. Visual representation of crime patterns assist analysts with in-depth understanding of crime behavior with time and location. The representation can be made more knowledgeable and perceptible by incorporating details of socio-economic factor and areafis geographical information providing insights to features that actually play role in certain crime pattern. To analyze the impact of these factors, two of the best density calculation clustering techniques i.e. Heat Maps and Hot Spots analysis are performed for Crime Against Person and Crime Against Property. The analysis demonstrated that Crimes Against Persons are more frequent in rural and sub-urban areas with mostly low socio-economic conditions; whereas, Crimes Against Property are mostly in commercial areas with mix socio-economic conditions.
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