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2013 IEEE 13th International Conference on Data Mining (2001)
San Jose, California
Nov. 29, 2001 to Dec. 2, 2001
ISBN: 0-7695-1119-8
pp: 163
ABSTRACT
We present GenMax, a backtrack search based algorithm for mining maximal frequent itemsets. GenMax uses a number of optimizations to prune the search space.It uses a novel technique called progressive focusing to perform maximality checking, and diffset propagation to perform fast frequency computation. Systematic experimental comparison with previous work indicates that different methods have varying strengths and weaknesses based on dataset characteristics. We found GenMax to be a highly efficient method to mine the exact set of maximal patterns.
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CITATION
Mohammed J. Zaki, Karam Gouda, "Efficiently Mining Maximal Frequent Itemsets", 2013 IEEE 13th International Conference on Data Mining, vol. 00, no. , pp. 163, 2001, doi:10.1109/ICDM.2001.989514
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