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在单向FP-tree上挖掘频繁闭项集
Mining frequent closed itemsets in unidirectional FP-tree
【摘要】 频繁闭项集提供了频繁项集的一种完整的、最小表示。针对稠密数据集,提出一种基于单向FP-tree的频繁闭项集挖掘算法Unid_FP-FCI。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来计算频繁闭项集的弊端,极大地降低了内存空间和时间开销,提高了挖掘效率。
【Abstract】 Frequent closed itemsets provide a minimal representation of frequent itemsets without losing their support information.This paper proposes an efficient algorithm Unid_FP-FCI for mining the complete set of frequent closed itemsets in a unidirectional FP-tree.Because in process of mining only generate constrained sub-trees consisting of three small arrays,which is pseudo tree structure based on the originally unidirectional FP-tree,the flaw is avoided in former algorithms which need to generate lots of conditional FP-trees for finding frequent closed itemsets recursively.Reducing the space and time consumption to a great extent,then the algorithm improve mining efficiency.
【Key words】 data mining; frequent itemset; frequent closed itemset; unidirectional FP-tree; constrained sub-tree;
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2008年10期
- 【分类号】TP301.6
- 【被引频次】11
- 【下载频次】169