Geometrically inspired itemset mining

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2006, Pages 655-666

  Verhein, Florian ^a   Chawla, Sanjay ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATION FUNCTIONS; FREQUENT ITEMSET MINING (FIM); ITEMVECTORS;

ALGEBRA; MATHEMATICAL TRANSFORMATIONS; NONLINEAR ANALYSIS;

DATA MINING;

EID: 49549103257     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2006.75     Document Type: Conference Paper

References (12)

1. D. Achlioptas. Database-friendly random projections. In Symposium on Principles of Database Systems, 2001.
2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proceedings of 20th International Conference on Very Large Data Bases VLDB, pages 487-499. Morgan Kaufmann, 1994.
3. Workshop on frequent itemset mining implementations 2003. http://fimi.cs.helsinki.fi/fimi03.
4. Workshop on frequent itemset mining implementations 2004. http://fimi.cs.helsinki.fi/fimi04.
5. J. Han, J. Pei, and Y. Yin. Mining frequent patterns without candidate generation. In 2000 ACM SIGMOD Intl. Conference on Management of Data, pages 1-12. ACM Press, May 2000.
6. F. Korn, A. Labrinidis, Y. Kotidis, and C. Faloutsos. Quantifiable data mining using ratio rules. VLDB Journal: Very Large Data Bases, 8(3-4):254-266, 2000.
7. F. Pan, G. Cong, A. Tung, J. Yang, and M. Zaki. Carpenter: Finding closed patterns in long biological datasets. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Morgan Kaufmann, 2003.
8. J. Pei, J. Han, and L. Lakshmanan. Pushing convertible constraints in frequent itemset mining. Data Mining and Knowledge Discovery: An International Journal, 8:227-252, May 2004.
9. J. Pei, J. Han, and R. Mao. CLOSET: An efficient algorithm for mining frequent closed itemsets. In ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pages 21-30, 2000.
10. S. Shekhar and Y Huang. Discovering spatial colocation patterns: A summary of results. Lecture Notes in Computer Science, 2121:236+, 2001.
11. M. Steinbach, P.-N. Tan, H. Xiong, and V. Kumar. Generalizing the notion of support. In The Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining KDD '04, 2004.
12. J. Wang and G. Karypis. Harmony: Efficiently mining the best rules for classification. In SIAM International Conference on Data Mining, pages 205-215, 2005.