| 基于FP-Tree的挖掘最大频繁项目集的新算法 |
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| 引用本文： | 杨青侠,何明祥,邱冬冬,聂宝军.基于FP-Tree的挖掘最大频繁项目集的新算法[J].中国科技信息,2012(14):88-89. |
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| 作者姓名： | 杨青侠 何明祥 邱冬冬 聂宝军 |
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| 作者单位： | 山东科技大学信息科学与工程学院,山东青岛,266000 |
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| 摘 要： | 挖掘最大频繁项目集是数据挖掘领域的一个重要的研究内容。Apriori算法作为一种挖掘频繁项目集的基本算法,其缺点是产生大量的候选项目集,算法的代价很大。本文在基于FP-Tree的基础上提出了挖掘最大频繁项目集的新算法FP-GDMA。该算法采用自顶向下和自底向上相结合的搜索策略有效减少了生产候选项目集的数目,有效提高了挖掘最大频繁项目集的效率。并通过实验比较FP-GDMA与DMFIA算法。
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| 关 键 词： | 最大频繁项目集 数据挖掘 FP-Tree FP-GDMA DMFIA |
A New Algorithm for Mining Maximum Frequent Itemsets Based on FP-Tree |
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| Yang Qingxia
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He Mingxiang
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Qiu Dongdong
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Nie Baojun.A New Algorithm for Mining Maximum Frequent Itemsets Based on FP-Tree[J].CHINA SCIENCE AND TECHNOLOGY INFORMATION,2012(14):88-89. |
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| Authors: | Yang Qingxia He Mingxiang Qiu Dongdong Nie Baojun |
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| Institution: | Yang Qingxia He Mingxiang Qiu Dongdong Nie Baojun College of Information Science and Engineering,Shandong University of Science and Technology,Qingdao,China |
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| Abstract: | Mining maximum frequent itemsets is an important research in data mining field.Apriori,as the basic algorithm for mining frequent itemsets,has drawbacks such as generating many candidate maximum frequent itemsets and tremendous cost.This paper proposes a new algorithm for mining maximum frequent itemsets named FP-GDMA based on FP-Tree.It uses the search strategy with combination of top-down and bottom-up,which effectively reduces the number of candidate frequent itemsets and effectively improves the efficiency for mining maximum frequent itemsets.The paper also compares FP-GDFM and DMFIA by experiment. |
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| Keywords: | Maximum Frequent Itemsets Data Mining FP-Tree FP-GDMA DMFIA |
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