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

Fingerprint

Frequent Pattern
Fault-tolerant
Mining
Apriori Algorithm
Frequent Pattern Mining
Fault tolerance
Fault Tolerance
Execution Time
Experimental Results

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

An efficient approach for mining fault-tolerant frequent patterns based on bit vector representations. / Koh, Jia-Ling; Yo, Pei Wy.

In: Lecture Notes in Computer Science, Vol. 3453, 19.09.2005, p. 568-575.

Research output: Contribution to journalConference article

@article{80a543bf72444dddb128dfa256688f11,
title = "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.",
author = "Jia-Ling Koh and Yo, {Pei Wy}",
year = "2005",
month = "9",
day = "19",
language = "English",
volume = "3453",
pages = "568--575",
journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
issn = "0302-9743",
publisher = "Springer Verlag",

}

TY - JOUR

T1 - An efficient approach for mining fault-tolerant frequent patterns based on bit vector representations

AU - Koh, Jia-Ling

AU - Yo, Pei Wy

PY - 2005/9/19

Y1 - 2005/9/19

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=24644484427&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=24644484427&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:24644484427

VL - 3453

SP - 568

EP - 575

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SN - 0302-9743

ER -