首页 | 本学科首页   官方微博 | 高级检索  
     

演变图上的连接子图演变模式挖掘
引用本文:邹兆年,高 宏,李建中,张 硕.演变图上的连接子图演变模式挖掘[J].软件学报,2010,21(4):1007-1019.
作者姓名:邹兆年  高 宏  李建中  张 硕
作者单位:哈尔滨工业大学 计算机科学与技术学院,黑龙江 哈尔滨 150001
基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60773063, 60933001, 60903017 (国家自然科学基 金); the National Basic Research Program of China under Grant No.2006CB303005 (国家重点基础研究发展计划(973)); the National Natural Science Foundation of China and the Research Grants Council of Hong Kong of China under Grant No.60831160525 (国家自然 基金委与香港资助局联合科研资助基金)
摘    要:探讨演变图(即随时间变化的图)的挖掘,重点研究在演变图中挖掘连接子图的演变模式集合.提出一种连 接子图的相似度函数及其快速计算算法.基于该相似度函数,提出一种发现演变模式集合的多项式时间复杂度的动 态规划算法.模拟数据集上的实验结果表明,该算法具有较低的误差率和较高的效率.真实数据集上的实验结果表 明,挖掘结果在真实应用中具有实际意义.

关 键 词:演变图  连接子图  演变模式
收稿时间:6/6/2008 12:00:00 AM

Mining Evolving Patterns of Connection Subgraphs over Evolving Graphs
ZOU Zhao-Nian,GAO Hong,LI Jian-Zhong and ZHANG Shuo.Mining Evolving Patterns of Connection Subgraphs over Evolving Graphs[J].Journal of Software,2010,21(4):1007-1019.
Authors:ZOU Zhao-Nian  GAO Hong  LI Jian-Zhong and ZHANG Shuo
Abstract:This paper investigates into the problem of mining evolving graphs, i.e. graphs changing over time. It focuses on mining evolving pattern set of connection subgraphs between given vertices in an evolving graph. A similarity function of connection subgraphs and the algorithm to compute it have been presented. Based on this similarity function, a dynamic programming algorithm with polynomial time complexity is proposed to find evolving pattern set. The experimental results on synthetic datasets show that the proposed algorithm has low error rate and high efficiency. The mining results on real datasets illustrate that the mining results have practical significance in real applications.
Keywords:evolving graph  connection subgraph  evolving pattern
点击此处可从《软件学报》浏览原始摘要信息
点击此处可从《软件学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号