Clustering of Crime Data using Haversine K-means Clustering Algorithm

Journal: GRENZE International Journal of Engineering and Technology
Authors: Sajna Mol H S, Gladston Raj S
Volume: 10 Issue: 1
Grenze ID: 01.GIJET.10.1.328_1 Pages: 762-766

Abstract

In this world, the rate of crimes is increasing as well as challenging the capabilities of people who are investigating crimes. Proper crime analysis and clustering has to be done in those cases. Crime analysis is the analysis of crime patterns and trends. It also assists in the research and planning necessary for the functioning of tactical forces and administrative services. Crime data grouping and clustering is very important to analyse the crime patterns and trends. By identifying patterns of crime committed in the past and the most common types of crime, crimes can be prevented from recurring in an area. Machine learning plays a key role in efficiently clustering today’s crime data

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