| 基于改进FP-树挖掘最大频繁模式 |
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| 引用本文： | 孟祥萍,王华金,缪秋滚.基于改进FP-树挖掘最大频繁模式[J].长春工程学院学报(自然科学版),2005,6(1):51-54,58. |
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| 作者姓名： | 孟祥萍 王华金 缪秋滚 |
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| 作者单位： | 长春工程学院,电气工程系,长春,130012;东北电力学院,研究生部,吉林,132012 |
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| 摘 要： | 由于挖掘密集型数据的频繁模式完全集非常困难 ,因而改进了传统的FP -树结构并提出了一种基于改进FP -树的最大频繁模式挖掘算法IFP -MAX ;通过引入后缀子树的概念 ,在挖掘过程中不用生成最大频繁模式候选集 ,大大提高了算法的时空效率。实验表明 ,IFP -MAX的挖掘速度比Miafia和GenMax快得多
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| 关 键 词： | 数据挖掘 关联规则 最大频繁模式 FP-树 |
| 文章编号： | 1009-8984(2005)01-0051-04 |
| 修稿时间： | 2004年10月9日 |
Mining maximal frequent patterns based on improved FP-tree |
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| MENG Xiang-ping,et al..Mining maximal frequent patterns based on improved FP-tree[J].Journal of Changchun Institute of Technology(Natural Science Edition),2005,6(1):51-54,58. |
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| Authors: | MENG Xiang-ping |
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| Abstract: | Because mining complete set of frequent patterns from dense database could be impractical, in this paper, the structure of a traditional FP-tree is improved and an algorithm (called IFP-MAX) for mining maximal frequent patterns based on improved FP-tree is proposed.By introducing the concept of postfix sub-tree, the proposed algorithm needn't generate the candidate of maximal frequent patterns in mining process and therefore greatly improves the mining efficiency in time and space scalability.Experimental results show that IFP-MAX is much faster than Mafia and GenMax. |
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| Keywords: | data mining association rule maximal frequent pattern FP-tree |
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