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International Journal
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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary
ISSN(Online):2349-7084 Submit Paper Check Paper Status Conference Proposal
1] Chen, M.S., Han,J.and Yu,P.S. 1996 Data mining – An overview from database perspective, IEEE Transaction on knowledge and data engineering 8 , 866-883 [2] Alm, E. and Arkin, A.P. 2003. Biological Networks, Current Opinion in Structural Biology 13(2), 193– 202. [3] Nijssen, S. and Kok, J., Faster association rules for multiple relations. In IJCAI’01: Seventeenth International Joint Conference on Artificial Intelligence, 2001, vol. 2, pp. 891–896. [4] Chuntao Jiang, Frans Coenen and Michele Zito, A Survey of Frequent Sub-graph Mining Algorithms:The Knowledge Engineering Review, Vol. 00:0, 1–31.c 2004. [5] A. Inokuchi, T.Washio, and H. Motoda. An apriori-based algorithm for mining frequent substructures from graph data. In PKDD’00. [6] J. Huan, W.Wang, and J. Prins. Efficient mining of frequent subgraph in the presence of isomorphism. UNC computer science technique report TR03-021, 2003. [7] J. Huan, W. Wang, J. Prins, and J. Yang. Spin: Mining maximal frequent sub-graphs from graph databases. UNC Technical Report TR04-018, 2004. [8] M. Kuramochi and G. Karypis. Grew-a scalable frequent subgraph discovery algorithm. In ICDM, pages 439–442,2004. [9] ZhaonianZou, Jianzhong Li, Hong Gao, and Shuo Zhang : Frequent Subgraph Patterns from Uncertain Graph Data. IEEE Transactions On Knowledge And Data Engineering, Vol. 22, No. 9, September 2010. [10] L. T. Thomas, S. R. Valluri, and K. Karlapalem. Margin:Maximal frequent subgraph mining. Proc. 6th IEEE Int’l Conf. Data mining (ICDM ’06), pp. 1097-1101, 2006. [11] Inokuchi, A., Washio, T., Nishimura, K. and Motoda, H. 2002. A Fast Algorithm for Mining Frequent Connected Subgraphs, Technical Report RT0448, IBM Research, Tokyo Research Laboratory, Japan. [12] Huan, J., Wang, W. and Prins, J. 2003. Efficient Mining of Frequent Subgraph in the Presence of Isomorphism, In Proceedings of the 2003 International Conference on Data Mining, 549-552.
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