Identifying relevant databases for multidatabase mining

Huan Liu, Hongjun Lu, Jun Yao

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

37 Scopus citations


Various tools and systems for knowledge discovery and data mining are developed and available for applications. However, when we are immersed in heaps of databases, an immediate question facing practitioners is where we should start mining. In this paper, breaking away from the conventional data mining assumption that many databases be joined into one, we argue that the first step for multidatabase mining is to identify databases that are most likely relevant to an application; without doing so, the mining process can be lengthy, aimless and ineffective. A relevance measure is thus proposed to identify relevant databases for mining tasks with an objective to find patterns or regularities about certain attributes. An efficient implementation for identifying relevant databases is described. Experiments are conducted to validate the measure’s performance and to show its promising applications.

Original languageEnglish (US)
Title of host publicationResearch and Development in Knowledge Discovery and Data Mining - 2nd Pacific-Asia Conference, PAKDD 1998, Proceedings
EditorsXindong Wu, Ramamohanarao Kotagiri, Kevin B. Korb
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3540643834, 9783540643838
StatePublished - 1998
Externally publishedYes
Event2nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 1998 - Melbourne, Australia
Duration: Apr 15 1998Apr 17 1998

Publication series

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


Other2nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 1998


  • Data mining
  • Multiple databases
  • Query
  • Relevance measure

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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