A fast algorithm for mining frequent subgraphs
一种快速的频繁子图挖掘算法

An algorithm for mining frequent subgraphs based on associated matrix was proposed. By normalizing the associated matrix of the graph, the computational cost on verifying the isomorphism of the subgraphs was effectively reduced. Based on the depth-first searching method, all the frequent subgraphs could be searched by adding edges progressively. Experimental results show that the algorithm has higher speed and better stability than other similar ones.