Out-of-core frequent pattern mining on a commodity PC

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2006, Issue , 2006, Pages 86-95

  Buehrer, Gregory ^a   Parthasarathy, Srinivasan ^a   Ghoting, Amol ^a  

^a Ohio State University   (United States)

Author keywords

Data mining; Itemsets; Out of core; Pattern mining; Secondary memory

Indexed keywords

ALGORITHMS; OPTIMIZATION; PATTERN RECOGNITION; PROBLEM SOLVING;

ITEMSETS; OUT OF CORE; PATTERN MINING; SECONDARY MEMORY;

DATA MINING;

EID: 33749561116     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150416     Document Type: Conference Paper

References (22)

1. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proceedings of the International Conference on Management of Data (SIGMOD), 1993.
2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proceedings of the International Conference on Very Large Data Bases (VLDB), 1994.
3. S. Brin, R. Motwani, and C. Silverstein. Beyond market basket: Generalizing association rules to correlations. In Proceedings of the International Conference on Management of Data (SIGMOD), 1997.
4. G. Buehrer, S. Parthasarathy, and A. Ghoting. Out of core frequent pattern mining on a commodity pc. In OSU Technical Report, volume OSU-CISRC-4/06-TR36, 2006.
5. D. Burdick, M. Calimlim, and J. Gehrke. MAFIA: A maximal frequent itemset mining algorithm for transactional databases. In Proceedings of the International Conference on Data Engineering (ICDE), 2001.
6. J. S. Chase, D. C. Anderson, P. N. Thakar, A. M. Vahdat, and R. P. Doyle. Managing energy and server resources in hosting centers. SIGOPS Oper. Syst. Rev., 35(5):103-116, 2001.
7. G. Dong and J. Li. Efficient mining of emerging patterns: Discovering trends and differences. In Proceedings of the International Conference on Knowledge Discovery and Data Mining (SIGKDD), 1999.
8. A. Ghoting, G. Buehrer, S. Parthasarathy, D. Kim, A. Nguyen, Y. Chen, and P. Dubey. Cache-conscious frequent pattern mining on a modern processor. In Proceedings of the International Conference on Very Large Data Bases (VLDB), pages 577-588, 2005.
9. B. Goethals and M. Zaki. Advances in frequent itemset mining implementations. In Proceedings of the ICDM workshop on frequent itemset mining implementations, 2003.
10. K. Gouda and M. Zaki. Efficiently mining maximal frequent itemsets. In Proceedings of the International Conference on Data Mining (ICDM), 2001.
11. G. Grahne and J. Zhu. Efficiently using prefix-trees in mining frequent itemsets. In Proceedings of the ICDM Workshop on Frequent Itemset Mining Implementations, 2003.
12. G. Grahne and J. Zhu. Mining frequent itemsets from secondary memory. In Proceedings of the International Conference on Data Mining (ICDM), 2004.
13. J. Han, J. Pei, and Y. Yin. Mining frequent patterns without candidate generation. In Proceedings of the International Conference on Management of Data (SIGMOD), 2000.
14. G. Liu, H. Lu, J. X. Yu, W. Wei, and X. Xiao. Afopt: An efficient implementation of pattern growth approach. In Proceedings of the ICDM workshop on frequent itemset mining implementations, 2003.
15. H. Mannila, H. Toivonen, and A. Verkamo. Discovery of frequent episodes in event sequences. Data Mining and Knowledge Discovery, 1997.
16. J. Park, M. Chen, and P. Yu. An effective hash-based algorithm for mining association rules. In Proceedings of the International Conference on Management of Data (SIGMOD), 1995.
17. S. Parthasarathy, M. Zaki, M. Ogihara, and W. Li. Memory placement techniques for parallel association mining. International Conference on Knowledge Discovery and Data Mining (SIGKDD), 1998.
18. S. Parthasarathy, M. Zaki, M. Ogihara, and W. Li. Parallel data mining for association rules on shared-memory systems. Knowledge and Information Systems Journal, 2001.
19. A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in large databases. In Proceedings of the International Conference on Very Large Data Bases (VLDB), 1995.
20. C. Silverstein, S. Brin, R. Motwani, and J. Ullman. Scalable techniques for mining causal structures. In Proceedings of the International Conference on Very Large Data Bases (VLDB), 1998.
21. M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery discovery of association rules. In Proceedings of the International Conference on Knowledge Discovery and Data Mining (SIGKDD), 1995.
22. J. Zhou, J. Cieslewicz, K. Ross, and M. Shah. Improving database performance on simultaneous multhithreading processors. In Proceedings of International Conference on Very Large Data Bases (VLDB), 2005.