SmartMiner: A Depth First Algorithm Guided by Tail Information for Mining Maximal Frequent Itemsets

Maximal frequent itemsets (MFI) are crucial to many tasks in data mining. Since the MaxMiner algorithm first introduced enumeration trees for mining MFI in 1998, there have been several methods proposed to use depth first search to improve performance. To further improve the performance of mining MFI, we proposed a technique to gather and pass tail (of a node) information to determine the next node to explore during the mining process. Our algorithm uses an augmented dynamic reordering heuristic with considering of the tail information. Compared with Mafia and GenMax, SmartMiner generates a much smaller search tree, requires a smaller number of support counting, and does not require superset checking. Using the datasets Mushroom and Connect, our experimental study reveals that SmartMiner generates the same MFI as Mafia and GenMax, but yields an order of magnitude improvement in speed.