Invented Predicates to Reduce Knowledge Acquisition

  • Hendra Suryanto
  • Paul Compton
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3257)


The aim of this study was to develop machine-learning techniques that would speed up knowledge acquisition from an expert. As the expert provided knowledge the system would generalize from this knowledge in order to reduce the need for later knowledge acquisition. This generalization should be completely hidden from the expert. We have developed such a learning technique based on Duce’s intra-construction and absorption operators [1] and applied to Ripple-Down Rule (RDR) incremental knowledge acquisition [2]. Preliminary evaluation shows that knowledge acquisition can be reduced by up to 50%.


Knowledge Acquisition Human Expert Absorption Operator Feature Construction Original Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Hendra Suryanto
    • 1
  • Paul Compton
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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