摘要
为减少频繁子图规范化检测的时间复杂度,对规范化邻接矩阵的相关性质进行分析。给出相关定理并证明其正确性,从而减少冗余候选子图的产生。在此基础上,提出一种频繁子图挖掘算法——FSM_CAM。实验结果证明,与现有频繁子图挖掘算法FSubGraphM相比,FSM_CAM算法的效率较高。
To reduce the frequent subgraph canonical detection time complexity,this paper discusses the relevant properties of the canonical adjacency matrix.In order to reduce the generation of redundant candidate subgraphs,it proposes the theorem to reduce redundancy candidate subgraph generation,and proves its correctness.Based on this,it proposes a frequent subgraph mining algorithms called FSM_CAM.Experimental results show that FSM_CAM algorithm＇s efficiency is greatly improved compared with existing frequent subgraph mining algorithms FsubGraphM.
出处
《计算机工程》
CAS
CSCD
2012年第7期31-33,共3页
Computer Engineering
基金
湖南省教育厅科研基金资助项目(10C0134)
湖南省教育厅基金资助重点项目(10A074)
湖南省自然科学基金资助项目(06JJ50107)
关键词
频繁子图
规范邻接矩阵
候选子图
数据挖掘
frequent subgraph
Canonical Adjacency Matrix（CAM）
candidate subgraph
data mining
