Efficiently Mining Maximal Frequent Itemsets. ICDM 2001
• 2001
Publication Information
Authors
Karam Gouda and Mohammed J. Zaki
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publication.type
International
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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.
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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