Asynchronous and anticipatory filter-stream based parallel algorithm for frequent itemset mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3202, Issue , 2004, Pages 422-433

  Veloso, Adriano ^a   Meira Jr , Wagner ^a   Ferreira, Renato ^a   Neto, Dorgival Guedes ^a   Parthasarathy, Srinivasan ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA FLOW ANALYSIS; DATA TRANSFER; FILTRATION; PARALLEL ALGORITHMS;

AGGREGATED INFORMATION; CANDIDATE GENERATION; COMMUNICATION OVERHEADS; CONSUMPTION RATES; FREQUENT ITEMSET MINING; PARALLEL PERFORMANCE; PRODUCTION RATES; STREAM PROGRAMMING;

ALGORITHMS;

EID: 33947410609     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30116-5_39     Document Type: Article

References (16)

1. A. Acharya, M. Uysal, and J. Satlz. Active disks: Programming model, algorithms and evaluation. In Proc. of the Intl. Conf. on Architectural Support for programming Languages and Operating Systems (ASPLOS VIII), pages 81-91. ACM Press, Oct 1998.
2. R. Agrawal and J. Shafer. Parallel mining of association rules. Transactions on Knowledge and Data Engineering, 8(6):962-969, 1996.
3. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. of the Intl. Conf. on Very Large Databases (VLDB), pages 487-499, SanTiago, Chile, June 1994.
4. M. Beynon, C. Chang, U. Catalyurek, T. Kurc, A. Sussman, H. Andrade, R. Ferreira, and J. Saltz. Processing large-scale multi-dimensional data in parallel and distributed environments. Parallel Computing, 28(5):827-859, 2002.
5. M. Beynon, T. Kurc, A. Sussman, and J. Saltz. Design of a framework for data-intensive wide-area applications. In Proc of the Heterogeneous Computing Workshop (HCW), pages 116-130. IEEE Computer Society Press, May 2000.
6. U. Catalyurek, M. Gray, T. Kurc, J. Saltz, and R. Ferreira. A component-based implementation of multiple sequence alignment. In Proc. of the ACM Symposium on Applied Computing (SAC), pages 122-126. ACM, 2003.
7. D. Cheung and Y. Xiao. Effect of data distribution in parallel mining of associations. Data Mining and Knowledge Discovery, 3(3):291-314, 1999.
8. E. Han, G. Karypis, and V. Kumar. Scalable parallel data mining for association rules. Transactions on Knowledge and Data Engineering, 12(3):728-737, 2000.
9. M. Joshi, E. Han, G. Karypis, and V. Kumar. Efficient parallel algorithms for mining associations. Parallel and Distributed Systems, 1759:418-429, 2000.
10. H. Mannila and H. Toivonen. Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery, 1(3):241-258, 1997.
11. S. Orlando, P. Palmerini, R. Perego, and F. Silvestri. An efficient parallel and distributed algorithm for counting frequent sets. In Proc. of the Intl. Conf. on Vector and Parallel Processing (VECPAR), pages 421-435, Porto, Portugal, 2002.
12. S. Parthasarathy, M. Zaki, M. Ogihara, and W. Li. Parallel data mining for association rules on shared-memory systems. Knowledge and Information Systems, 3(1):1-29, 2001.
13. M. Spencer, R. Ferreira, M. Beynon, T. Kurc, U. Catalyurek, A. Sussman, and J. Saltz. Executing multiple pipelined data analysis operations in the grid. In Proc. of the ACM/IEEE Conf. on Supercomputing, pages 1-18. IEEE Computer Society Press, 2002.
14. A. Veloso, M. Otey, S. Parthasarathy, and W. Meira. Parallel and distributed frequent itemset mining on dynamic datasets. In Proc. of the High Performance Computing Conference (HiPC), Hyderabad, India, December 2003. Springer and ACM-SIGARCH.
15. M. Zaki and K. Gouda. Fast vertical mining using diffsets. In Proc. of the Int. Conf. on Knowledge Discovery and Data Mining (SIGKDD). ACM, August 2003.
16. M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New parallel algorithms for fast discovery of association rules. Data Mining and Knowledge Discovery, 4(1):343-373, December 1997.