Distributed mining of maximal frequent itemsets on a data grid system

Journal of Supercomputing

Volumn 37, Issue 1, 2006, Pages 71-90

  Luo, Congnan ^a   Pereira, Anil L ^a   Chung, Soon M ^a  

^a Wright State University   (United States)

Author keywords

Association rules; Data Grid; Distributed data mining; Maximal frequent itemsets; Scalability

Indexed keywords

ALGORITHMS; COMMUNICATION; COMPUTER WORKSTATIONS; DATA MINING; DATA STRUCTURES; DATABASE SYSTEMS; SYNCHRONIZATION;

ASSOCIATION RULES; DATA GRID; DISTRIBUTED DATA MINING; MAXIMAL FREQUENT ITEMSETS; SCALABILITY;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 33745697934     PISSN: 09208542     EISSN: 15730484     Source Type: Journal    
DOI: 10.1007/s11227-006-5210-7     Document Type: Article

References (21)

1. R. C. Agarwal, C. C. Aggarwal, and V. V. V. Prasad. Depth first generation of long patterns. In Proc. of the 6th ACM SIGKDD Int'I Conf. on Knowledge Discovery and Data Mining, 108-118, 2000.
2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. of the 20th VLDB Conf., 487-499, 1994.
3. R. Agrawal and J. C. Sharer. Parallel mining of association rules. IEEE Trans. on Knowledge and Data Engineering, 8(6):962-969, 1996.
4. R. J. Bayardo. Efficient mining long patterns from databases. In Proc. of the ACM SIGMOD Int'I Conf. on Management of Data, 85-93, 1998.
5. A. Bayucan, R. L. Henderson, J. P. Jones, C. Lesiak, B. Mann, and T. Proett. Portable batch system: external reference specification. Release PBS Pro 5.0, Veridian Systems, Inc., 2000.
6. . D. Burdick, M. Calimlim, and J. Gehrke. MAFIA: a maximal frequent itemset algorithm for transaction databases. In Proc. of Int'l Conf. on Data Engineering, 443-452, 2001.
7. R. Butler, V. Welch, D. Engert, I. Foster, S. Tuecke, J. Volmer, and C. Kesselman. A national-scale authentication infrastructure. IEEE Computer, 33(12):60-66, 2000.
8. A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke. The data grid: towards an architecture for the distributed management and analysis of large scientific datasets. Journal of Network and Computer Applications, 23(3): 187-200, 2001.
9. D. W. Cheung, S. D. Lee, and Y. Xiao. Effect of data skewness and workload balance in parallel data mining. IEEE Trans. on Knowledge and Data Engineering, 14(3):498-514, 2002.
10. S. M. Chung and J. Yang. A parallel distributive join algorithm for cube-connected multiprocessors. IEEE Trans. on Parallel and Distributed Systems, 7(2):127-137, 1996.
11. K. Czajkowski, I. Foster, N. Karonis, C. Kesselman, S. Martin, W. Smith, and S. Tuecke. A resource management architecture for metacomputing systems. In Proc. of the Workshop on Job Scheduling Strategies for Parallel Processing, 62-82, 1998.
12. E. H. Han, G. Karypis, and V. Kumar. Scalable parallel data mining for association rules. IEEE Trans. on Knowledge and Data Engineering, 12(3):337-352, 2000.
13. I. Foster and C. Kesselman. The globus toolkit, in The Grid: Blueprint for a New Computing Infrastructure, I. Foster and C. Kesselman (Eds.), Morgan Kaufmann, 259-278, 1999.
14. I. Foster, C. Kesselman, and S. Tuecke. The anatomy of the grid: enabling scalable virtual organizations. Int'I Journal of Supercomputer Applications and High-Performance Computing, 15(3):200-222, 2001.
15. I. Foster, C. Kesselman, J. M. Nick, and S. Tuecke. Grid services for distributed system integration. IEEE Computer, 35(6):37-46, 2002.
16. I. Foster and R. L. Grossman. Data integration in a bandwidth-rich world. Communications of the ACM, 46(11):51-57, 2003.
17. K. Gouda and M. J. Zaki. Efficiently mining maximal frequent itemsets. In Proc. of the 1st IEEE Int'I Conf. on Data Mining, 163-170, 2001.
18. N.T. Karonis, B. Toonen, and I. Foster. MPICH-G2: a grid-enabled implementation of the message passing interface. Journal of Parallel and Distributed Computing, 63(5):551-563, 2003.
19. M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery of association rules. Computer Science Department Technical Report #651, The University of Rochester, 1997.
20. M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. Parallel algorithms for fast discovery of association rules. Data Mining and Knowledge Discovery, 1(4):343-373, 1997.
21. M. J. Zaki. Scalable algorithms for association mining. IEEE Trans. on Knowledge and Data Engineering, 12(3):372-390, 2000.