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Received:January 28, 2015 Revised:March 18, 2015
Received:January 28, 2015 Revised:March 18, 2015
中文摘要: 互联网的发展使有组织犯罪集团的认定与处罚变的更为困难. 针对有组织犯罪集团的特点, 采用共犯网络结构分析和数据挖掘技术相结合的方法确定有组织犯罪集团结构及其组成实体, 提出一种对有组织犯罪集团进行系统分析和挖掘的新算法. 该算法能从大型真实犯罪数据集提取信息, 快速获取有组织犯罪集团证据, 提高了有组织犯罪集团检测效率. 最后将算法与其他现有算法进行比较, 实验结果表明该算法的时间性能优越.
Abstract:It is more difficult that cognizance and punishment of organized crime groups with development of the Internet. According to the characteristics of the organized crime groups, we are using co-offending networks analysis methods and data mining techniques to identifying organized crime structures and their constituent entities. An novel algorithm for mining organized crime groups is proposed. The goal of our work is to improve the efficiency of the organized crime detection for extracting information from large real-life crime datasets to obtain evidence of the organized crime group. Experimental results show that the algorithm of time performance is superior compared with other existing algorithms.
keywords: organized crime groups co-offending matrix mining technology crime evidence time performance
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基金项目:国家高技术研究发展计划(863)(2012AA112312);教育部高等学校博士学科点专项科研基金(20110161120006);湖南省公安厅科研基金(湘公科信明电(2013)56号);湖南省教育规划课题(XJK013CXX012)
引用文本：
唐德权,史伟奇,凌志刚.有组织犯罪集团挖掘算法.计算机系统应用,2015,24(9):196-200
TANG De-Quan,SHI Wei-Qi,LING Zhi-Gang.Algorithm for Ming Organized Crime.COMPUTER SYSTEMS APPLICATIONS,2015,24(9):196-200
唐德权,史伟奇,凌志刚.有组织犯罪集团挖掘算法.计算机系统应用,2015,24(9):196-200
TANG De-Quan,SHI Wei-Qi,LING Zhi-Gang.Algorithm for Ming Organized Crime.COMPUTER SYSTEMS APPLICATIONS,2015,24(9):196-200
