Analyzing and Displaying of Crime Hotspots using Fuzzy Mapping Method
نویسندگان
چکیده
Pattern detection is one of the essential challenges in crime mapping and analysis. Data mining can be used to explore crime detection problems. A cluster technique is an effective method for determining areas with high concentrations of localized events. Conversely, it remains a particularly demanding task to detect hotspots with mapping methods in view of the vulnerability connected with the suitable number of groups to create and additionally securing significance of individual clusters identified. Fuzzy clustering means algorithm was used for identifying hotspots of Chicago police department's citizen law enforcement analysis and reporting system data. In fuzzy clustering, a membership value to each data is assigned, which indicate the strength of relationship between that data points and a specific cluster. In this study each cluster represented the group of global positioning system data points having latitude and longitude as their co-ordinates. The findings from this study were expected to aware the public about crime hotspots. Law enforcement agencies can take prior steps to prevent crime with the use of detected crime hotspots.
منابع مشابه
Vol.52 (AICT 2014), pp.81-85
Law enforcement agencies use various crime analysis tools to discover crimes. However, a big volume of crime data has made the process of analyzing crimes difficult. Previously proposed methods only consider improving the productivity of the detectives and other law enforcement agencies. In this paper, we argue that the crime analysis methods should be also useful for citizen, and propose a use...
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