Early warning system based on data mining to identify crime patterns

Abstract

The analysis of criminal information is critical for the purpose of preventing the occurrence of offenses, so the crime records committed in the past are analyzed including perpetrators. The main objective was to identify crime patterns in the city of Bogota, Colombia, supported using Early Warning System based on data mining (CRISP-DM method). The research results show the identification of 12 different criminal profiles demonstrating that the Early Warning System is applicable since it managed to significantly reduce the time devoted to the processes of registering complaints and searching for criminal profiles.