An efficient approach for mining fault-tolerant frequent patterns based on bit vector representations

Authors:
Jia-Ling Koh;Pei-Wy Yo
Affiliations:
Department of Information and Computer Education, National Taiwan Normal University, Taipei, Taiwan;Department of Information and Computer Education, National Taiwan Normal University, Taipei, Taiwan
Venue:
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Year:
2005

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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.