Efficient mining of association rules in large dynamic databases

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

Volumn 1405, Issue , 1998, Pages 49-63

  Omiecinski, Edward ^a   Savasere, Ashok ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ASSOCIATION RULES; DATA MINING;

ASSOCIATION MINING; DYNAMIC DATABASE; LARGE DATABASE; MINING ALGORITHMS; MINING ASSOCIATIONS; MINING OF ASSOCIATION RULES; MINING PROBLEMS; PARTITION ALGORITHMS;

DATABASE SYSTEMS;

EID: 67449122477     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/BFb0053471     Document Type: Conference Paper

References (7)

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2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In Proceedings of the 20th International Conference on Very Large Data Bases, Santiago, Chile, August 29-September 1 1994.
3. J. Han and Y. Fu. Discovery of multiple-level association rules from large databases. In Proceedings of the VLDB Conference, pages 420-431, September 1995.
4. M. Houtsma and A. Swami. Set-oriented mining of association rules. In Proceedings of the International Conference on Data Engineering, Taipei, Taiwan, March 1995.
5. J. S. Park, M-S. Chen, and P. S. Yu. An effective hash based algorithm for mining association rules. In Proceedings of the ACM-SIGMOD Conference on Management of Data, pages 229-248, San Jose, California, May 1995.
6. A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in large databases. In Proceedings of the 21st International Conference on Very Large Data Bases, pages 688-192, Zurich, Swizerland, August 1995.
7. A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in large databases. Technical Report GIT-CC-95-04, Georgia Institute of Technology, Atlanta, GA 30332, January 1995.