Mining closed and maximal frequent subtrees from databases of labeled rooted trees

IEEE Transactions on Knowledge and Data Engineering

Volumn 17, Issue 2, 2005, Pages 190-202

  Chi, Yun ^a   Xia, Yi ^a   Yang, Yirong ^a   Muntz, Richard R ^a  

^a Engineering IV   (United States)

Author keywords

Closed frequent subtree; Data mining; Frequent subtree; Graph algorithms; Maximal frequent subtree; Mining methods and algorithms; Trees

Indexed keywords

CLOSED FREQUENT SUBTREE; FREQUENT SUBTREE; GRAPH ALGORITHMS; MAXIMAL FREQUENT SUBTREE; MINING METHODS;

ALGORITHMS; COMPUTER NETWORKS; CORRELATION METHODS; DATA MINING; DATABASE SYSTEMS; HEURISTIC METHODS; PARAMETER ESTIMATION; PATTERN RECOGNITION; XML;

TREES (MATHEMATICS);

EID: 14644411753     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2005.30     Document Type: Article

References (28)

1. T. Asai, K. Abe, S. Kawasoe, H. Arimura, H. Satamoto, and S. Arikawa, "Efficient Substructure Discovery from Large Semi-Structured Data," Proc. Second SIAM Int'l Conf. Data Mining, Apr. 2002.
2. T. Asai, H. Arimura, T. Uno, and S. Nakano, "Discovering Frequent Substructures in Large Unordered Trees," Proc. Sixth Int'l Conf. Discovery Science, Oct.-. 2003.
3. R. Chalmers and K. Almeroth, "On the Topology of Multicast Trees," technical report, Univ. of California, Santa Barbara, Mar. 2002.
4. Y. Chi, Y. Yang, and R.R. Muntz, "Canonical Forms for Labeled Trees and Their Applications in Frequent Subtree Mining," Knowledge and Information Systems, to appear.
5. Y. Chi, Y. Yang, and R.R. Muntz, "Indexing and Mining Free Trees," Proc. Int'l Conf. Data Mining (ICDM '03), Nov. 2003.
6. Y. Chi, Y. Yang, and R.R. Muntz, "HybridTreeMiner: An Efficient Algorithm for Mining Frequent Rooted Trees and Free Trees Using Canonical Forms," Proc. 16th Int'l Conf. Scientific and Statistical Database Management (SSDBM '04), June 2004.
7. Y. Chi, Y. Yang, Y. Xia, and R.R. Muntz, "CMTreeMiner: Mining Both Closed and Maximal Frequent Subtrees," Proc. Eighth Pacific Asia Conf. Knowledge Discovery and Data Mining (PAKDD '04), May 2004.
8. J. Cui, J. Kim, D. Maggiorini, K. Boussetta, and M. Gerla, "Aggregated Multicast-A Comparative Study," Proc. IFIP Networking Conf. 2002, May 2002.
9. M.R. Garey and D.S. Johnson, Computers and Intractability-A Guide to the Theory of NP-Completeness. New York: W.H. Freeman, 1979.
10. J. Han, J. Pei, and Y. Yin, "Mining Frequent Patterns without Candidate Generation," Proc. Int'l Conf. Management of Data (ACM SIGMOD '00), May 2000.
11. J. Hein, T. Jiang, L. Wang, and K. Zhang, "On the Complexity of Comparing Evolutionary Trees," Discrete Applied Math., vol. 71, pp. 153-169, 1996.
12. J. Huan, W. Wang, and J. Prins, "Efficient Mining of Frequent Subgraph in the Presence of Isomorphism," Proc. Int'l Conf. Data Mining (ICDM '03), 2003.
13. A. Inokuchi, T. Washio, and H. Motoda, "An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data," Proc. Fourth European Conf. Principles and Practice of Knowledge Discovery in Databases (PKDD '00), pp. 13-23, Sept. 2000.
14. T. Kudo, "FREQT: An Implementation of FREQT," http:// chasen.org/~taku/software/freqt/, 2003.
15. M. Kuramochi and G. Karypis, "Frequent Subgraph Discovery," Proc. Int'l Conf. Data Mining (ICDM '01), Nov. 2001.
16. F. Luccio, A.M. Enriquez, P.O. Rieumont, and L. Pagli, "Bottom-Up Subtree Isomorphism for Unordered Labeled Trees," Technical Report TR-04-13, Università di Pisa, 2004.
17. S. Nijssen and J.N. Kok, "Efficient Discovery of Frequent Unordered Trees," Proc. Int'l Workshop Mining Graphs, Trees, and Sequences, 2003.
18. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, "Discovering Frequent Closed Itemsets for Association Rules," Lecture Notes in Computer Science, vol. 1540, pp. 398-416, 1999.
19. U. Rückert and S. Kramer, "Frequent Free Tree Discovery in Graph Data," Special Track on Data Mining, Proc. ACM Symp. Applied Computing (SAC '04), 2004.
20. D. Shasha, J.T.L. Wang, and S. Zhang, "Unordered Tree Mining with Applications to Phylogeny," Proc. 20th Int'l Conf. Data Eng., 2004.
21. C. Wang, M. Hong, J. Pei, H. Zhou, W. Wang, and B. Shi, "Efficient Pattern-Growth Methods for Frequent Tree Pattern Mining," Proc. Eighth Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD '04), 2004.
22. K. Wang and H. Liu, "Discovering Typical Structures of Documents: A Road Map Approach," Proc. 21st Int'l Conf. Research and Development in Information Retrieval (ACM SIGIR '98), pp. 146-154, 1998.
23. Y. Xiao, J-F Yao, Z. Li, and M. Dunham, "Efficient Data Mining for Maximal Frequent Subtrees," Proc. Int'l Conf. Data Mining (ICDM'03), Nov. 2003.
24. X. Yan and J. Han, "gSpan: Graph-based Substructure Pattern Mining," Proc. Int'l Conf. Data Mining (ICDM '02), 2002.
25. X. Yan and J. Han, "CloseGraph: Mining Closed Frequent Graph Patterns," Proc. Int'l Conf. Knowledge Discovery and Data Mining (SIGKDD'03), 2003.
26. L.H. Yang, M.L. Lee, W. Hsu, and S. Achary, "Mining Frequent Quer Patterns from XML Queries," Proc. Eighth Int'l Conf. Database Systems for Advanced Applications (DASFAA '03), 2003.
27. M.J. Zaki, "Efficiently Mining Frequent Trees in a Forest," Proc. Eighth Int'l Conf. Knowledge Discovery and Data Mining (ACM SIGKDD '03), July 2002.
28. M.J. Zaki and C.C. Aggarwal, "XRules: An Effective Structural Classifier for XML Data," Proc. Int'l Conf. Knowledge Discovery and Data Mining (SIGKDD '03), 2003.