【摘要】 FP-growth算法是一种被证明有效的频繁模式挖掘算法。但是由于在挖掘频繁模式时需要递归地生成大量的条件FP-树,其时空效率较低,本文针对这一问题,首先构造一种改进的TFP-树结构,然后在构造的TFP-tree基础上引入被约束子树提出一种基于TFP树的频繁项集的改进挖掘算法,并对该算法进行性能分析,结果证明该算法在运行速度得到很大提高。更多还原

【Abstract】 FP-growth algorithm is a frequent pattern mining algorithm which has been proved to be efficiency.But this algorithm must generate a huge number of conditional FP-trees recursively in process of mining,so the efficiency of FP-growth remains un-satisfactory.In this paper,an improved TFP-tree frame was built firstly,then introducing constrained sub tree in the base of TFP-tree.Finally,an improved frequent pattern mining algorithm based on const rained TFP-tree is proposed,at the same time a per-formance analysis was carried out.The result proved that this algorithm’s run speed was improved a lot.更多还原