Interaction of Crime Risk across Crime Types in Hotspot Areas

Repeat and near-repeat victimization are important concepts in the study of crime. The incidence repeat offenses within a single type crime has been confirmed. However, circumstances existing across types requires further investigation. This article investigates whether phenomenon exists different by studying spread risk types. Taking Suzhou City as research area, DBSCAN-based algorithm is proposed, which can detect large number stable hotspots through multi-density self-adaptation parameters. Pearson correlation used to analyze between In hotspots, among also different. After occurs, identifying aid prevention.