资 源 简 介
FP-Growth is a recursive mining algorithm for frequent patterns. With each recursion, a new FP-tree and the corresponding header table are built. This paper proposes another approach to improve the mining efficiency: only one FP-tree is constructed, and instead of building new trees in every recursion, builds new header tables; frequent patterns are generated along the way, so we call this algorithm “header table recursion (HTR)” method. Tests show that it will get better performance for relative small datasets because the compress of the FP-tree has no significant impact on the performance yet inflicts extra time cost in tree creation operations. However on larger datasets, the traversal of the original FP-tree will become more time-consuming and its overall performance needs further testing.
