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