计算机技术与发展2011，Vol.21Issue(11)：89-91,95,4.
基于图数据挖掘算法的犯罪规律研究及应用
Research and Application on Crime Rule Based on Graph Data Mining Algorithm
摘要
Abstract
The data mining technologies applying to analyze the crime rule has become a hot spot in field of the public security information system, there is little work being done on analyzing the crime rule of criminal and terrorist groups. Compared with other data technology , graph can express richer semantic meaning. It is a new paradigm to apply based on graph data mining algorithm to analyze the crime rules. To mine crime rule and key members of a crime group, first proposed theory based on graph data mining, then proposed a frequent subgraph of same crime characteristics based algorithm called GDMCR (Graph Data Mining Crime Rule ), finally employed frequent subgraph analysis techniques to discover crime rule and key structure. The experimental results show the efficiency and usability of the crime rule analysis system based on graph data mining, and demonstrate that GDMCR is efficient.关键词
数据挖掘/频繁子图/犯罪规律/核心成员/关联知识Key words
data mining/frequent subgraph/crime rule/key members/association knowledge分类
信息技术与安全科学引用本文复制引用
唐德权,张悦,贺永恒,肖自红..基于图数据挖掘算法的犯罪规律研究及应用[J].计算机技术与发展,2011,21(11):89-91,95,4.基金项目
湖南省教育厅资助科研项目(10C0134) （10C0134）
湖南省自然科学基金(06JJ50107) （06JJ50107）
湖南省教育厅重点项目基金(10A074) （10A074）
