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Crime Hotspot Feature Mining Of Burglary Based On Element Analysis

Posted on:2022-10-24Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q GuoFull Text:PDF
GTID:2506306482965609Subject:Security engineering
Abstract/Summary:
In the context of the rapid advancement of social prosperity,with the introduction and implementation of smart policing strategies,targeted crime prevention and control have become an important direction of public security work.Crime hotspot can represent the characteristic and aggregation pattern of crime in spatial distribution.Mining the feature and formation of crime hotspot can help the police prevent crimes in advance and accurately fight crimes.At present,there have been a lot of researches on crime hotspot,but most of them focus on the identification and explanation of formation mechanism.There is a lack of in-depth analysis and excavation of the feature and formation of criminal activities at the internal spatial scale of the hotspot.Aiming at the deficiencies in previous studies,we design a method to explore the feature of hotspot from the perspective of criminal behavior and environmental structure,and explain its causes.Therefore,taking case elements and environmental elements as basic variables,we build a labeling system of elements,and propose a method for mining the hotspot feature based on element analysis,in order to dig out the hidden feature of hotspot.Using this method,we take the burglary cases in Beijing for example to conduct an empirical analysis experiment.Firstly,through the quantification of labels,we compared the crime hotspots in Beijing from the perspective of semantic.The results suggest that the environmental structure characteristics of the five hotspots in Beijing have certain differences.Although the specific attraction factors are different,the degree of attraction to offenders is similar.The differences in the behavior characteristic of offender indicate that the formation of some hotspots may be caused by offenders repeating crimes.Secondly,the composition of cases in hotspots is analyzed,and the degree to which offenders in the hotspots are affected by empirical and environmental factors is compared to describe the feature and formation of hotspots.The results suggest that most of cases located within the crime hotspots in Beijing are repeats and near repeats.The hotspot where the offenders are affected by empirical factors are more likely to originate from the repeated crimes committed in the area,while the hotspot where the offenders are affected by environmental factors are more likely to originate from different offenders committing crimes in the area.The method can conduct a more in-depth exploration of crime hotspots and obtain more refined hotspot features.We hope this method can aid decisionmaking on crime prevention and detection in policing.
Keywords/Search Tags:Crime Hotspot, Near repeat, Label System, Semantic Mining, Quantitative Analysis
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