| 在单向FP—tree上挖掘最大频繁项集 |
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| 引用本文： | 宋晶晶,姜保庆,关丽霞.在单向FP—tree上挖掘最大频繁项集[J].电脑与微电子技术,2010(1):19-24. |
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| 作者姓名： | 宋晶晶 姜保庆 关丽霞 |
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| 作者单位： | [1]清远职业技术学院,清远511510 [2]河南大学数据与知识工程研究所,开封475004 |
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| 基金项目： | 河南省高校杰出科研人才创新工程项目（No.2007KYCX018） |
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| 摘 要： | 针对稠密数据集．提出一种基于单向FP—tree的最大频繁项集挖掘算法Unid_FP-Max2。该算法在挖掘过程中只生成被约束子树，而它是一种虚拟的树结构，在原有的单向FP—tree基础上用三个很小的数组来表示．因而避免了以往算法需递归构造条件FP—tree来计算最大频繁项集的弊端，极大的降低了内存空间和时间开销，提高了挖掘效率。实验表明，与FP—Max算法相比。算法的效率提高了1倍以上。
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| 关 键 词： | 数据挖掘 频繁项集 最大频繁项集 单向FP—tree 被约束子树 |
Mining Maximal Frequent Itemsets in a Unidirectional FP-tree |
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| Authors: | SONG Jing-jing JIANG Bao-qing GUAN Li-xia |
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| Affiliation: | 1. Qingyuan Polytechnic, Qingyuan 511510; 2. Institute of Data and Knowledge Engineering, Henan University, Henan 475004) |
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| Abstract: | Proposes an efficient algorithm Unid_FP-Max2 for mining the complete set of maximal frequent itemsets in a unidirectional FP-tree. Because the algorithm only generates constrained sub-trees which is pseudo tree structure consisting of three small arrays based on the originally unidirectional FP-tree, avoides the flaw in former algorithms which need to generate lots of conditional FP-trees for finding maximal frequent itemsets recursively. Reduces the space and time consumption to a great extent,then the algorithm improves mining efficiency. Experiment shows that in comparison with FP-Max, this algorithm accelerates the mining speed by at least one times. |
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| Keywords: | Data Mining Frequent Itemset Maximal Frequent Itemset Unidirectional FP-tree Constrained Sub-Tree |
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