Towards efficient data re-mining (DRM)

Jiming Liu, Jian Yin

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

8 Citations (Scopus)

Abstract

The problem that we tackle here is a practical one: When users interactively mine association rules, it is often the case that they have to continuously tune two thresholds: minimum support and minimum confidence, which describe the users' changing requirements. In this paper, we present an efficient data re-mining (DRM) technique for updating previously discovered association rules in light of threshold changes.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 5th Pacific-Asia Conference, PAKDD 2001, Proceedings
EditorsDavid Cheung, Graham J. Williams, Qing Li
PublisherSpringer Verlag
Pages406-412
Number of pages7
ISBN (Print)3540419101, 9783540419105
DOIs
Publication statusPublished - 2001
Event5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001 - Hong Kong, Hong Kong
Duration: 16 Apr 200118 Apr 2001
https://link.springer.com/book/10.1007/3-540-45357-1 (Conference Proceedings)

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2035
ISSN (Print)0302-9743

Conference

Conference5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001
Country/TerritoryHong Kong
CityHong Kong
Period16/04/0118/04/01
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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