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    An efficient algorithm for mining complete share-frequent itemsets using BitTable and heuristics
    (2012-01-01)
    Nawapornanan, Chayanan
    ;
    Boonjing, Veera
    This paper proposes a new efficient algorithm for mining share-frequent itemsets from BitTable knowledge - extracted once from a transaction database. The knowledge contains sufficient information for such a mining task and provides efficient interactive access. The algorithm finds all share-frequent itemsets by level-wise generating complete promising candidates from a BitTable using heuristics and testing for desired solutions. Simulation results reveal that the proposed algorithm perform significantly better than ShFSM and DCG both runtime and a number of generated candidates. © 2012 IEEE.