An efficient algorithm for dense regions discovery from large-scale data streams

Andy M. Yip, Edmond H. Wu, Michael K. Ng, Tony F. Chan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 8th Pacific-Asia Conference, PAKDD 2004, Proceedings
EditorsHonghua Dai, Ramakrishnan Srikant, Chengqi Zhang
PublisherSpringer Verlag
Pages116-120
Number of pages5
ISBN (Print)354022064X, 9783540220640
DOIs
StatePublished - 2004
Externally publishedYes
Event8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004 - Sydney, Australia
Duration: May 26 2004May 28 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3056
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2004
Country/TerritoryAustralia
CitySydney
Period05/26/0405/28/04

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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