计算机工程2011，Vol.37Issue(20)：27-29,32,4.DOI:10.3969/j.issn.1000-3428.2011.20.010
一种新的频繁子图挖掘算法
New Algorithm of Mining Frequent Subgraph
摘要
Abstract
In order to resolve the problem of traditional Apriori algorithm that exists redundancy subgraphs when mining frequent subgraph, a new frequent subgraph mining algorithm called GAI is proposed. To reduce the number of scanning database, MADI index structure of three levels is proposed to store the information of graphs. It uses the expansion of the Etree to construct the frequent graph, and uses tables to store candidate subgraphs. It is avoided the redundancy subgraphs in expansion processing and scanning the entire database. It greatly simplifies the calculation of support degree and improves the query efficiency of graph isomorphism and subgraph isomorphism. Experimental results show GAI has the higher mining efficiency than Apriori algorithm.关键词
Apriori算法/数据挖掘/子图同构/频繁子图Key words
Apriori algorithm/ data mining/ subgraph isomorphism/ frequent subgraph分类
信息技术与安全科学引用本文复制引用
敦景峰,张伟,柴然..一种新的频繁子图挖掘算法[J].计算机工程,2011,37(20):27-29,32,4.基金项目
国家自然科学基金资助项目(60673136) （60673136）
河北省应用基础重点研究项目(10963527D) （10963527D）
