论文信息 - Mining Online GIS for Crime Rate and Models based on Frequent Pattern Analysis

Mining Online GIS for Crime Rate and Models based on Frequent Pattern Analysis

— The researchers proposed to develop a mechanism in mining an Online Graphical Information System (GIS) for crime rate and models using frequent pattern analysis. It is a web-based system that includes GIS for robbery, homicide and physical injury incidents within Iloilo City. This system can help police identify where and what time crime frequently happen. It generates who are the frequent victims in the community. The main focus of the proposed system is the analysis of frequent crime patterns and its association rules and crime hot spots. Results show the hot spots which displays clustered crimes in the Google Map. It uses the Google Heat Map layer in clustering plotted crimes. These hot spots are showing the density of crime. Furthermore, the system is able to generate frequent patterns of crimes. This uses Apriori algorithm in generating the results.

John David Elijah Sandig | Ruby Mae Somoba

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