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An Efficient Approach for Mining Fault-Tolerant Frequent Patterns Based on Bit Vector Representations

机译:基于位矢量表示的挖掘容错频繁模式的有效方法

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In this paper, an algorithm, called VB-FT-Mine (Vectors-Based Fault-Tolerant frequent patterns Mining), is proposed for mining fault-tolerant frequent patterns efficiently. In this approach, fault-tolerant appearing vectors are designed to represent the distribution that the candidate patterns contained in data sets with fault-tolerance. VB-FT-Mine algorithm applies depth-first pattern growing method to generate candidate patterns. The fault-tolerant appearing vectors of candidates are obtained systematically, and the algorithm decides whether a candidate is a fault-tolerant frequent pattern quickly by performing vector operations on bit vectors. The experimental results show that VB-FT-Mine algorithm has better performance on execution time significantly than FT-Apriori algorithm proposed previously.
机译:本文提出了一种称为VB-FT-MINE(基于vB的容错频繁模式采矿)的算法,用于有效地用于挖掘容错频繁模式。在这种方法中,容错出现的向量被设计为表示具有容错容限中的数据集中包含的候选模式的分布。 VB-FT-MIN算法应用深度第一模式生长方法以生成候选模式。系统地获得候选者的容错载体,并且算法通过在比特向量上执行矢量操作来决定候选是一种容错频繁模式。实验结果表明,VB-FT-ine算法在比先前提出的FT-APRIORI算法显着的执行时间具有更好的性能。

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