Discovering Frequent Itemsets in the Presence of Highly Frequent Items

Author:

Groth Dennis P.,Robertson Edward L.

Publisher

Springer Berlin Heidelberg

Reference14 articles.

1. Agarwal, R. C., Aggarwal, C. C., and Prasad, V. V. Depth first generation of long patterns. In SIGKDD 2000, Proceedings ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 20-23, 2000, Boston, MA,USA (2000), ACM Press, pp. 108–118.

2. Agrawal, R., and Srikant, R. Fast algorithms for mining association rules in large databases. In VLDB’94, Proceedings of 20th International Conference on Very Large Data Bases, September 12-15, 1994, Santiago de Chile, Chile (1994), J. B. Bocca, M. Jarke, and C. Zaniolo, Eds., Morgan Kaufmann, pp. 487–499.

3. Bayardo Jr., R. J. Efficiently mining long patterns from databases. In SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA (1998), L. M. Haas and A. Tiwary, Eds., ACM Press, pp. 85–93.

4. Bayardo Jr., R. J., Agrawal, R., and Gunopulos, D. Constraint-based rule mining in large, dense databases. In Proceedings of the 15th International Conference on Data Engineering, 23-26 March 1999, Sydney, Austrialia (1999), IEEE Computer Society, pp. 188–197.

5. Brin, S., Motwani, R., and Silverstein, C. Beyond market baskets: Generalizing association rules to correlations. In SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13-15, 1997, Tucson, Arizona, USA (1997), J. Peckham, Ed., ACM Press, pp. 265–276.

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