Association Rule Mining on Crime Pattern Mining

Abstract

Recognizing similar offenses during a offender inquiry is a major position of offense analysts. Through the help of pattern finding technique, crime specialists discover new pattern types from dataset. Over the past few years, association rule mining is implemented to analyze crime data from real datasets to find exact trends in crime. The indicated paper has worked with the (FP Growth algorithm) to determine similar crime patterns. Observational results are presented that will help crime experts predict crime and determine the maximum chances of corruption in a particular area.