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

Jia-Ling Koh, Pei Wy Yo

研究成果: 雜誌貢獻會議論文同行評審

13 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)568-575
頁數8
期刊Lecture Notes in Computer Science
3453
出版狀態已發佈 - 2005 九月 19
事件10th International Conference on Database Systems for Advanced Applications, DASFAA 2005 - Beijing, 中国
持續時間: 2005 四月 172005 四月 20

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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