%0 Journal Article
%T Fast hybrid evolutionary substructure discovery algorithm<br>快速的混合进化子结构发现算法
%A CHANG Xin-gong
%A MA Shang-cai
%A JIA Wei
%A <br>常新功
%A 马尚才
%A 贾伟
%J 计算机应用
%D 2009
%I 
%X To avoid local-optima and enhance the qualities of solutions, a hybrid evolutionary algorithms system was developed to perform data mining on databases represented as graphs. To increase the efficiency of the algorithm, a new substructure extension method based on single-label substructure extension was proposed, which could greatly reduce the times for performing graph isomorphism during the evolution. Experimental results on some typical data sets and theoretical proof indicate its high efficiency and correctness.
%K evolutionary algorithm
%K graphical data mining
%K substructure discovery
%K substructure extension<br>进化算法
%K 图数据挖掘
%K 子结构发现
%K 子结构扩展
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=57B52E474518E27C716CE98F79136E70&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=B31275AF3241DB2D&sid=15863C3A31AE2538&eid=B0D0FAC45E96482A&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=8