A Method for Closed Frequent Subgraph Mining in a Single Large Graph

Mining frequent subgraphs is an interesting and important problem in the graph mining field, that from a single large has been strongly developed, recently attracted many researchers. Among them, MNI-based approaches are considered as state-of-the-art, such GraMi algorithm. Besides subgraph (FSM), closed was also developed. This practical applications fundamental premise for studies. paper proposes CloGraMi (Closed Frequent Subgraph Mining) algorithm based on to find all graph. Two effective strategies first one new level order traversal strategy quickly determine searching process, second setting condition early pruning portion of non-closed candidates, both them aim reduce running time well memory requirements, improve performance proposed Our experiments performed five real datasets (both directed undirected graphs) results show requirements our significantly better than those GraMi-based