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

Jia-Ling Koh, Pei Wy Yo

Research output: Contribution to journalConference article

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)568-575
Number of pages8
JournalLecture Notes in Computer Science
Volume3453
Publication statusPublished - 2005 Sep 19
Event10th International Conference on Database Systems for Advanced Applications, DASFAA 2005 - Beijing, China
Duration: 2005 Apr 172005 Apr 20

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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