document: CloseGraph : mining closed frequent graph patterns Recent research on pattern discovery has progressed form mining frequent itemsets and sequences to mining structured patterns including trees , lattices , and graphs . As a general data structure , graph can model complicated relations among data with wide applications in bioinformatics , Web exploration , and etc. . However , mining large graph patterns in challenging due to the presence of an exponential number of frequent subgraphs . Instead of mining all the subgraphs , we propose to mine closed frequent graph patterns . A graph g is closed in a database if there exists no proper supergraph of g that has the same support as g. A closed graph pattern mining algorithm , CloseGraph , is developed by exploring several interesting pruning methods . Our performance study shows that CloseGraph not only dramatically reduces unnecessary subgraphs to be generated but also substantially increases the efficiency of mining , especially in the presence of large graph patterns .
doc_bio_tags: O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O