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

  • David Wai-lok Cheung
  • Ada Wai-Chee Fu
  • Jiawei Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 869)


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 rule-based 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.


learning and adaptive systems knowledge discovery in databases rule-based concept generalization attribute-oriented induction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • David Wai-lok Cheung
    • 1
  • Ada Wai-Chee Fu
    • 2
  • Jiawei Han
    • 3
  1. 1.Department of Computer ScienceThe University of Hong KongHong Kong
  2. 2.Department of Computer ScienceChinese University of Hong KongHong Kong
  3. 3.School of Computing ScienceSimon Fraser UniversityCanada

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