| 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 |
| DOI： |
| 分类号: |
| 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) |
|
| Mining Evolving Patterns of Connection Subgraphs over Evolving Graphs |
|
ZOU Zhao-Nian,GAO Hong,LI Jian-Zhong,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. |
| Key words: evolving graph connection subgraph evolving pattern |
