An automated crime pattern detection using k-means clustering
by S. Babu Renga Rajan; K.G. Srinivasagan; K. Ramar; S. Meenachi Sunderasan
International Journal of Advanced Operations Management (IJAOM), Vol. 3, No. 3/4, 2011

Abstract: In the information era, data handling is one of the toughest tasks and very essential. In current scenario, the management and engineering principles must bring into play a vital role to handle the real time application data in resolving law and order cases. Especially crime and police department is showing keen interest to utilise the data mining techniques with computing power to analyse the crime information and identify different patterns of crime. The annual report of the Indian Ministry of Home Affairs states that the conviction rate is 42.3% and 52.7% of cases are pending. In Indian scenario, hectic manual works are involved and it takes huge amount of time for identifying the crime type and to narrow down the number of suspected criminals. This paper proposed a novel automated crime information system using k-means clustering to identify the crime and categorise the same.

Online publication date: Tue, 30-Sep-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Operations Management (IJAOM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com