An Approach for Crime Rate Prediction Using Data Mining
Journal: International Journal of Computer Science and Mobile Applications IJCSMA (Vol.7, No. 4)Publication Date: 2019-04-30
Authors : P.D.Patil; P.H.Patil; S.N.Isani; R.R.Jagtap; L.M.Koli; D.B.Shukla;
Page : 9-16
Keywords : Data mining; k-means; Cluster; Clustering; Crime Analysis;
Abstract
Crime rate is increasing now-a-days in many countries. There may be several types of crimes that occurs like murder, sexual assault, traffic violence, burglary etc. This higher crime rate must be reduced. For reducing the rate of crime we propose a system in which earlier or existing data is imported into system or admin will enter whole dataset and data mining algorithm such as k-means algorithm is used for clustering to predict the crime information. Algorithm will cluster collaboration and dissolution of organized crime groups, identifying various relevant crime patterns and analysis of crime data. Clustering will be done on the basis of location, gang or time. To determine position, time, location or gang related with all type of crime. The system will help to prevent crime occurring in society.
Other Latest Articles
- Shearing Invariant Texture Descriptor from a Local Binary Pattern and its Application in Paper Fingerprinting
- THE MAHATMA OF COMMUNICATION
- A Decision Support System Using Demographic Issues: A Case Study in Turkey
- A Feature Model Metrics-Based Approach to Develop a Software Product Line
- Skyline Recommendation in Distributed Networks
Last modified: 2019-05-08 19:54:08