On computing, storing and querying frequent patterns

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

Volumn , Issue , 2003, Pages 607-612

  Liu, Guimei ^a   Lu, Hongjun ^a   Lou, Wenwu ^a   Yu, Jeffrey Xu ^b  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Data mining and data warehousing; Frequent pattern mining

Indexed keywords

BASIC BUILDING BLOCK; DATA WAREHOUSING; DISK-BASED; EFFICIENT ALGORITHM; EXPERIMENTAL STUDIES; FREQUENT PATTERN MINING; FREQUENT PATTERN TREE; FREQUENT PATTERNS; ITEM CONSTRAINT; LARGE DATASETS; MINIMUM SUPPORT; MINING TASKS; STORED PATTERN; TIME-CONSUMING PROCESS; TRANSACTIONAL DATABASE; TREE CONSTRUCTION;

ALGORITHMS; DATA MINING; DATA STRUCTURES; DATA WAREHOUSES; WAREHOUSES;

TREES (MATHEMATICS);

EID: 36849025073     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/956750.956827     Document Type: Conference Paper

References (17)

1. R. Agrawal, T. Imielinski, and A. N. Swami. Mining association rules between sets of items in large databases. In SIGMOD, 1993.
2. S. Brin, R. Motwani, J. D. Ullman, and S. Tsur. Dynamic itemset counting and implication rules for market basket data. In SIGMOD, 1997.
3. J. Han, J. Pei, and Y. Yin. Mining frequent patterns without candidate generation. In SIGMOD, 2000.
4. G. Liu, H. Lu, Y. Xu, and J. X. Yu. Ascending frequency ordered prefix-tree: Efficient mining of frequent patterns. In DASFAA, 2003.
5. J. Liu, Y. Pan, K. Wang, and J. Han. Mining frequent item sets by opportunistic projection. In SIGKDD, 2002.
6. T. Morzy and M. Zakrzewicz. Group bitmap index: A structure for association rules retrieval. In SIGKDD, 1998.
7. J. S. Park, M. Chen, and P. S. Yu. An effective hash based algorithm for mining association rules. In SIGMOD, 1995.
8. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Discovering frequent closed itemsets for association rules. In ICDT, 1999.
9. J. Pei, J. Han, H. Lu, S. Nishio, S. Tang, and D. Yang. H-mine: Hyper-structure mining of frequent patterns in large databases. In ICDM, 2001.
10. J. Pei, J. Han, and R. Mao. Closet: An efficient algorithm for mining frequent closed itemsets. In DMKD, 2000.
11. R. C. Agarwal, C. C. Aggarwal, and V. V. V. Prasad. A tree projection algorithm for finding frequent itemsets. Journal on Parallel and Distributed Computing, 61 (3):350-371, 2001.
12. A. Savasere, E. Omiecinski, and S. B. Navathe. An efficient algorithm for mining association rules in large databases. In VLDB, 1995.
13. A. Tuzhilin and B. Liu. Querying multiple sets of discovered rules. In SIGKDD, 2002.
14. J. Wang, J. Pei, and J. Han. Closet+: Searching for the best strategies for mining frequent closed itemsets. In SIGKDD, 2003.
15. M. J. Zaki and C. Hsiao. Charm: An efficient algorithm for closed itemset mining. 2002.
16. M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery of association rules. In SIGKDD, 1997.
17. Z. Zheng, R. Kohavi, and L. Mason. Real world performance of association rule algorithms. In SIGKDD, 2001.