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

Abstract

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.