Knowledge discovery in databases: A rule-based attribute-oriented approach

David Wai Lok Cheung, Ada Wai Chee Fu, Jiawei Han

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


An attribute-oriented induction has been developed in the previous study of knowledge discovery in databases. A concept tree ascension technique is applied in concept generalization. In this paper, we extend the background knowledge representation from an unconditional non-rule-based concept hierarchy to a rule-based concept hierarchy, which enhances greatly its representation power. An efficient rulebased attribute-oriented induction algorithm is developed to facilitate learning with a rule-based concept graph. An information loss problem which is special to rule-based induction is described together with a solution suggested.

Original languageEnglish (US)
Title of host publicationMethodologies for Intelligent Systems - 8th International Symposium, ISMIS 1994, Proceedings
EditorsZbigniew W. Ras, Maria Zemankova
Number of pages9
ISBN (Print)9783540584957
StatePublished - 1994
Externally publishedYes
Event8th International Symposium on Methodologies for Intelligent Systems, ISMIS 1994 - Charlotte, United States
Duration: Oct 16 1994Oct 19 1994

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume869 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other8th International Symposium on Methodologies for Intelligent Systems, ISMIS 1994
Country/TerritoryUnited States


  • Attribute-oriented induction
  • Knowledge discovery in databases
  • Learning and adaptive systems
  • Rule-based concept generalization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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