Verifying and mining frequent patterns from large windows over data streams

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2008, Pages 179-188

  Mozafari, Barzan ^a   Thakkar, Hetal ^a   Zaniolo, Carlo ^a  

^a Department of Civil and Environmental Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATIVE PROCESSING; CHLORINE COMPOUNDS; COMPUTATIONAL COMPLEXITY; DATA MINING; LEARNING SYSTEMS; MINING; MINING ENGINEERING; TECHNOLOGY; WINDOWS;

ASSOCIATION RULES; DATA ENGINEERING; DATA STREAMING; FREQUENT ITEMSET MINING; FREQUENT PATTERNS; HASH TREES; INTERNATIONAL CONFERENCES; MINING FREQUENT ITEMSETS; MINING TASKS; RUNNING TIME; SLIDING WINDOWS; STATE-OF-THE-ART METHODS; TIME RESPONSES; VERIFICATION ALGORITHMS; WINDOW SIZES;

TREES (MATHEMATICS);

EID: 52649129706     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2008.4497426     Document Type: Conference Paper

References (25)

1. R. Agrawal and R. Srikant, "Fast algorithms for mining association rules in large databases," in VLDB, 1994.
2. J. Han, J. Pei, and Y. Yin, "Mining frequent patterns without candidate generation," in SIGMOD, 2000.
3. R. Srikant and R. Agrawal, "Mining sequential patterns: Generalizations and performance improvements," in EDBT, 1996.
4. J. Yu, Z. Chong, H. Lu, Z. Zhang, and A. Zhou, "A false negative approach to mining frequent itemsets from high speed transactional data streams." Inf. Sci., 2006.
5. M. J. Zaki and C. Hsiao, "CHARM: An efficient algorithm for closed itemset mining," 2002.
6. H. Toivonen, "Sampling large databases for association rules," in VLDB, 1996, pp. 134-145.
7. J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal, and M. Hsu, "Mining sequential patterns by pattern-growth: The PrefixSpan approach," IEEE TKDE, vol. 16, no. 11, pp. 1424-1440, November 2004.
8. R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan, "Automatic subspace clustering of high dimensional data for data mining applications," in SIGMOD, 1998.
9. B. Liu, W. Hsu, and Y. Ma, "Integrating classification and association rule mining," in KDDM, 1998.
10. K. Wang, S. Zhou, and S. C. Liew, "Building hierarchical classifiers using class proximity," in VLDB, 1999, pp. 363-374.
11. J. Li, D. Maier, K. Tufte, V. Papadimos, and P. Tucker, "No pane, no gain: efficient evaluation of sliding-window aggregates over data streams." SIGMOD Record, 2005.
12. Y. Bai, H. Thakkar, H. Wang, C. Luo, and C. Zaniolo, "A data stream language and system designed for power and extensibility." in CIKM, 2006, pp. 337-346.
13. N. Jiang and L. Gruenwald, 'Cfi-stream: mining closed frequent itemsets in data streams," in SIGKDD, 2006.
14. N. Jiang and L. Gruenwald, "Research issues in data stream association rule mining," SIGMOD Record, 2006.
15. W. Cheung and O. R. Zaiane, "Incremental mining of frequent patterns without candidate generation or support," in DEAS, 2003. [Online]. Available: citeseer.ist.psu.edu/622682.html
16. C-S. Leung, Q. Khan, and T Hoque, "Cantree: A tree structure for efficient incremental mining of frequent patterns," in ICDM, 2005.
17. Y. Chi, H. Wang, P. S. Yu, and R. R. Muntz, "Moment: Maintaining closed frequent itemsets over a stream sliding window," in Proceedings of the 2004 IEEE International Conference on Data Mining (ICDM'04), November 2004.
18. J. Pei, J. Han, and R. Mao, "CLOSET: An efficient algorithm for mining frequent closed itemsets," in SIGMOD, 2000.
19. J. S. Park, M.-S. Chen, and P. S. Yu, "An effective hash-based algorithm for mining association rules," in SIGMOD, 1995, pp. 175-186.
20. S. Brin, R. Motwani, J. D. Ullman, and S. Tsur, "Dynamic itemset counting and implication rules for market basket data," in SIGMOD, 1997, pp. 255-264.
21. B. Mozafari, H. Thakkar, and C. Zaniolo, "Verifying and mining frequent patterns from large windows over data streams," University of California Los Angeles, Tech. Rep. 070021, 2007.
22. "Frequent itemset mining dataset repository, http://fimi.cs. helsinki.fi/data/." [Online], Available: http://fimi.cs.helsinki.fi/data/
23. J. Koh and S. Shieh, "An efficient approach for maintaining association rules based on adjusting fp-tree structures." in DASFAA, 2004.
24. A. Evfimievski, J. Gehrke, and R. Srikant, "Limiting privacy breaches in privacy preserving data mining," in PODS, 2003.
25. S. Agrawal, J. Krishnan, and J. Haritsa, "On addressing efficiency concerns in privacy-preserving mining." in DASFAA, 2004, pp. 113-124.