Paper Info
Title
Data Mining for Prevention of Crimes.
Abstract
Preemptive measures are of utmost importance for crime prevention. Law enforcement agencies need to have an agile approach to solve everchanging crimes. Data analytics has proven to be an effective deterrent in the field of crime data analysis. Various countries like the United States of America have benefitted by this approach. The Government of India has also taken an initiative to implement data analytics to facilitate crime prevention measures. In this research paper, we have used R Studio, an open source data mining tool to perform the data analysis on the crime dataset shared by the Gujarat Police Department. To develop predictive model and study crime patterns we used various supervised and unsupervised data mining techniques such as Multiple Linear Regression, K-Means Clustering and Association Rules Analysis. The scope of this research paper is to showcase the effectiveness of data mining in the domain of crime prevention. In addition, an effort has been put forth to help the Gujarat Police Department to analyze their crime records and provide meaningful insights for decision making to solve the cases recorded.
Year
Venue
Field
2018
HCI
Data mining,Data analysis,Computer science,Source data,Association rule learning,Law enforcement,Cluster analysis,Crime prevention,Government,Crime analysis
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
8
3
Name
Order
Citations
PageRank
Neetu Singh1109.56
Chengappa Bellathanda Kaverappa200.34
Jehan D. Joshi300.34