计算机工程2016，Vol.42Issue(11)：207-212,6.DOI:10.3969/j.issn.1000-3428.2016.11.034
一种提高遗传算法子图挖掘效率的数据结构
A Data Structure for Improving Sub Graph Mining Efficiency of Genetic Algorithm
摘要
Abstract
In order to improve the sub graph mining efficiency of Genetic Algorithm(GA)in complex network,this paper designs a new data structure,which is named Adjacency Tree(AT).There is double-tree structure in AT,which is developed from the chain structure in Adjacency List (AL ).It means that the head-nodes and list-nodes of original adjacency list are both organized by AVL tree.AT reduces time complexity to O (lb (n2 )) and space complexity to O(n).Based on the experiment on datasets of biological networks and social networks with Multi-objective Genetic Algorithm(MOGA),experimental result shows that AT achieves better mining performance compared with the AL and Orthogonal List(OL)in large datasets,and it also has better generality.关键词
邻接树/复杂网络/子图挖掘/数据结构/遗传算法Key words
Adjacency Tree(AT)/complex network/sub graph mining/data structure/Genetic Algorithm(GA)分类
信息技术与安全科学引用本文复制引用
刘先锋,郭林沅..一种提高遗传算法子图挖掘效率的数据结构[J].计算机工程,2016,42(11):207-212,6.基金项目
湖南省教育厅科学研究基金（16C0956）；湖南省重点学科建设基金。 （）
