标题:Analyses of Crime Patterns in NIBRS Data Based on a Novel Graph Theory Clustering Method: Virginia as a Case Study
作者:Zhao, Peixin; Darrah, Marjorie; Nolan, Jim; Zhang, Cun-Quan
作者机构:[Zhao, Peixin] Shandong Univ, Sch Management, Jinan, Shandong, Peoples R China.; [Darrah, Marjorie; Zhang, Cun-Quan] W Virginia Univ, Dept Math, Mor 更多
通讯作者:Zhao, PX
通讯作者地址:[Zhao, PX]Shandong Univ, Sch Management, Jinan, Shandong, Peoples R China.
来源:SCIENTIFIC WORLD JOURNAL
出版年:2014
DOI:10.1155/2014/492461
摘要:This paper suggests a novel clustering method for analyzing the National Incident-Based Reporting System (NIBRS) data, which include the determination of correlation of different crime types, the development of a likelihood index for crimes to occur in a jurisdiction, and the clustering of jurisdictions based on crime type. The method was tested by using the 2005 assault data from 121 jurisdictions in Virginia as a test case. The analyses of these data show that some different crime types are correlated and some different crime parameters are correlated with different crime types. Theanalyses also show that certain jurisdictions within Virginia share certain crime patterns. This information assists with constructing a pattern for a specific crime type and can be used to determine whether a jurisdiction may be more likely to see this type of crime occur in their area.
收录类别:SCOPUS;SCIE;SSCI
WOS核心被引频次:1
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897552979&doi=10.1155%2f2014%2f492461&partnerID=40&md5=fed6fd54974b76e75df625e12374cb15
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