Approximately mining recently representative patterns on data streams

Jia-Ling Koh, Yuan Bin Don

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding window, the frequency changing point (FCP) method was proposed for monitoring the recent occurrences of itemsets in a data stream under the assumption that exact one transaction arrives at each time point. In this paper, the FCP method is extended for maintaining recent patterns in a data stream where a block of various numbers of transactions (including zero or more transactions) is inputted within each time unit. Moreover, to avoid generating redundant information in the mining results, the recently representative patterns are discovered from the maintained structure approximately. The experimental results show that our approach reduces the run-time memory usage significantly. Moreover, the proposed GFCP algorithm achieves high accuracy of mining results and guarantees no false dismissal occurring.

Original languageEnglish
Title of host publicationEmerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers
Pages231-243
Number of pages13
Publication statusPublished - 2007 Dec 1
EventPacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007 - Nanjing, China
Duration: 2007 May 222007 May 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4819 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherPacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007
CountryChina
CityNanjing
Period07/5/2207/5/22

Fingerprint

Data Streams
Transactions
Mining
Frequent Itemsets
Sliding Window
Data storage equipment
High Accuracy
Monitoring
Unit
Zero
Experimental Results

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Koh, J-L., & Don, Y. B. (2007). Approximately mining recently representative patterns on data streams. In Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers (pp. 231-243). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4819 LNAI).

Approximately mining recently representative patterns on data streams. / Koh, Jia-Ling; Don, Yuan Bin.

Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers. 2007. p. 231-243 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4819 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Koh, J-L & Don, YB 2007, Approximately mining recently representative patterns on data streams. in Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4819 LNAI, pp. 231-243, Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, Nanjing, China, 07/5/22.
Koh J-L, Don YB. Approximately mining recently representative patterns on data streams. In Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers. 2007. p. 231-243. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Koh, Jia-Ling ; Don, Yuan Bin. / Approximately mining recently representative patterns on data streams. Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers. 2007. pp. 231-243 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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