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MAFIA: a maximal frequent itemset algorithm for transactional databases
Proceedings 17th International Conference on Data Engineering
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very long. The search strategy of our algorithm integrates a depth-first traversal of the itemset lattice with effective pruning mechanisms. Our implementation of the search strategy combines a vertical bitmap representation of the database with an efficient relative bitmap compression schema. In a thorough experimental
doi:10.1109/icde.2001.914857
dblp:conf/icde/BurdickCG01
fatcat:xuxgxgy2ofhxfihktlpefzagle