CRIME PREDICTION BY K-MEANS ALGORITHM FOR CPLC

Abstract

Crime analysis and prevention is a systematic approach for identifying and analyzing patterns and trends in crime. With the increasing advent of computerized systems, crime data analysts can help the Law enforcement officers to speed up the process of solving crimes. About 10% of the criminals commit about 50% of the crimes. Even though we cannot predict who all may be the victims ofcrime but can predict the place that has probability for its occurrence. Our system can predict the attributes and some traits that will be common among the criminals. K-means algorithm is done by partitioning data into groups based on their means. K-means algorithm has an extension called expectation - maximization algorithm where we partition the data based on their parameters. This easy to implement data mining framework works with the geospatial plot ofcrime and helps to improve the productivity ofthe detectives and other law enforcement officers. This system is designed with an attempt to implement it in the Sindh Police Department and Citizen Police Liaison Committee (CPLC).