[1]
Zhang X., Zhao C. F., and Wang P., Mining link patterns in linked data, presented at the 13th International Conference on Web Age Information Management, Harbin, China, 2012.
[2]
Sheth A., Aleman-Meza B., Arpinar B., Bertram C., Warke Y. S., and Ramakrishnan C., Semantic association identification and knowledge discovery for national security applications, Journal of Database Management, vol. 16, no. 1, pp. 33–53, 2005.
[3]
Basse A., Gandon F., Mirbel I., Lo M., and Mirbel I., DFS-based frequent graph pattern extraction to characterize the content of RDF triple stores, presented at the Web Science Conference 2010: Extending the Frontiers of Society Online, Raleigh, USA, 2010.
[4]
Yan X. F. and Han J. W., Gspan: Graph-based substructure pattern mining, presented at the 2002 IEEE International Conference on Data Mining, Maebashi, Japan, 2002.
[5]
Yan X. F. and Han J. W., CloseGraph: Mining closed frequent graph patterns, presented at the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington DC, USA, 2003.
[6]
Wang J., Hsu W., Lee M. L., and Sheng C., A partition-based approach to graph mining, presented at the 22nd International Conference on Data Engineering, Atlanta, GA, USA, 2006.
[7]
Inokuchi A., Washio T., and Motoda H., An apriori-based algorithm for mining frequent substructures from graph data, presented at the 4th European Symposium on the Principle of Data Mining and Knowledge Discovery, Lyon, France, 2000.
[8]
Nijssen S. and Kok J. A., Quickstart in frequent structure mining can make a difference, presented at the 10th ACM SIGKDD International Conference on Kowledge Discovery in Databases (KDD04), Seattle, WA, USA, 2004.
[9]
Holder L. B., Cook D. J., and Djoko S., Substructure discovery in the subdue system, in Proceedings of the AAAI94 Workshop Knowledge Discovery in Databases, Seattle, WA, USA, 1994.
[10]
Huan J., Wang W., and Prins J., Efficient mining of frequent subgraph in the presence of isomorphism, presented at the 3rd International Conference on Data Mining, Melbourne, FL, USA, 2003.
[11]
Huan J., Wang W., Prins J., and Yang J., Spin: Mining maximal frequent subgraphs from graph databases, presented at the 10th ACM SIGKDD International Conference on Knowledge Discovery in Databases, Seattle, WA, USA, 2004.
[12]
Karypis G. and Kumar V., Multilevel algorithms for multiconstraint graph partitioning, in Proceedings of the ACM/IEEE Conference on Supercomputing, 1998, pp. 343-348.
[13]
Wang C., Wang W., Pei J., Zhu Y., and Shi B., Scalable mining of large disk-based graph databases, presented at the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Orlando, FL, USA, 2004.
[14]
Nguyen S. N., Orlowska M. E., and Li X., Graph mining based on a data partitioning approach, presented at the 19th Conference on Australasian Databases, Wollongong, Australia, 2008.
