在单向FP-tree上挖掘频繁闭项集

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。

Mining frequent closed itemsets in unidirectional FP-tree

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.