Title: An automated crime pattern detection using k-means clustering

Authors: S. Babu Renga Rajan; K.G. Srinivasagan; K. Ramar; S. Meenachi Sunderasan

Addresses: PET Engineering College, Tiruchendur Raod, Vallioor, Tamilnadu – 627117, India. ' National Engineering College, KR Nagar, Kovilpatti, Tamilnadu – 628503, India. ' Einstein Engineering College, Sir C.V. Raman Nagar, Seethaparpanalur, Tirunelveli, Tamilnadu – 627012, India. ' Manonmanium Sundaranar University, Abesekapatti, Tirunelveli, Tamilnadu – 627012, India

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.

Keywords: crime patterns; clustering; data mining; k-means; law enforcement; semi-supervised learning; India; law and order; police departments; criminals; crime information systems.

DOI: 10.1504/IJAOM.2011.045455

International Journal of Advanced Operations Management, 2011 Vol.3 No.3/4, pp.220 - 229

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 14 Feb 2012 *

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