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Received:June 03, 2016 Revised:July 07, 2016
Received:June 03, 2016 Revised:July 07, 2016
中文摘要: 本文基于公安业务中的治安防控原理,构建了面向情报分析和决策指挥的犯罪情报数据挖掘框架.首先,对案事件数据库进行预处理和空间编码的基础上得到标准化的案件信息数据,随后,利用聚类分析、关联分析和分类分析中的相关方法可得到治安案件的时空风险、重点人特征和作案手段特征等信息.通过对北京市实际盗窃案件数据进行挖掘,证明了数据挖掘技术能够很好的应用于犯罪情报的分析.
Abstract:This paper builds a framework about the crime data mining of on intelligence analysis and decision command based on the principle of prevention and control in public security. First, we can get the standardized crime information according to the preprocessing of crime database and space encoding. Using the related methods used in cluster analysis, classification and association analysis, we can get such information as the spatial-temporal risk distribution of crime, targeted people features and modus-operandi. Finally, by mining the data of actual theft cases in Beijing, it is proved that data mining methods could play significant role in crime intelligence analysis.
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基金项目:国家“十二五”科技支撑计划项目(2015BAK12B03);中国人民公安大学基本科研业务费项目(2016JKF01211)
引用文本:
陈鹏,瞿珂,胡啸峰.犯罪情报分析中的数据挖掘应用.计算机系统应用,2017,26(2):249-253
CHEN Peng,QU Ke,HU Xiao-Feng.Application of Data Mining in Criminal Intelligence Analysis.COMPUTER SYSTEMS APPLICATIONS,2017,26(2):249-253
陈鹏,瞿珂,胡啸峰.犯罪情报分析中的数据挖掘应用.计算机系统应用,2017,26(2):249-253
CHEN Peng,QU Ke,HU Xiao-Feng.Application of Data Mining in Criminal Intelligence Analysis.COMPUTER SYSTEMS APPLICATIONS,2017,26(2):249-253