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。
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 unsatisfactory. 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 TFPtree 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 .
出处
《微计算机信息》
北大核心
2007年第33期139-140,97,共3页
Control & Automation
基金
教育部基金资助项目(03023)
