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First IEEE International Conference on Data Mining (ICDM'01)
Efficiently Mining Maximal Frequent Itemsets
San Jose, California
November 29-December 02
ISBN: 0-7695-1119-8
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.
Citation:
Karam Gouda, Mohammed J. Zaki, "Efficiently Mining Maximal Frequent Itemsets," icdm, pp.163, First IEEE International Conference on Data Mining (ICDM'01), 2001
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