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Combining Cases and Rules to Provide Contextualised Knowledge Based Systems

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Modeling and Using Context (CONTEXT 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2116))

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Abstract

Providing contextualised knowledge often involves the difficult and time-consuming task of specifying the appropriate contexts in which the knowledge applies. This paper describes the Ripple Down Rules (RDR) knowledge acquisition and representation technique which does not attempt to define up front the possible context/s. Instead cases and the exception structure provide the context and rules provide the index by which to retrieve the case/s. K.A is incremental. The domain expert locally patches rules as new cases are seen. Thus. RDR is a hybrid case-based and rule-based approach. The use of Formal Concept Analysis to translate the RDR performance system into a formal context and uncover an explanation system in the form of an abstraction hierarchy further strengthens our emphasis on the combined use of cases and rules to provide contextualised knowledge.

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Author information

Authors and Affiliations

  1. Department of Computing. Division of Information and Communication Sciences, Macquaric University, Sydney

    Debbie Richards

Authors
  1. Debbie Richards
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Bilkent, Ankara, 06533, Turkey

    Varol Akman

  2. Department of Computer and Management Sciences, University of Trento, 38100, Trento, Italy

    Paolo Bouquet

  3. Philosophy Department, University of Michigan, 2251 Angell Hall, Ann Arbor, MI, 48109-1003, USA

    Richmond Thomason

  4. Philosophy Department, University of Dundee, Dundee, DD1 4HN, Scotland, UK

    Roger Young

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© 2001 Springer-Verlag Berlin Heidelberg

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Richards, D. (2001). Combining Cases and Rules to Provide Contextualised Knowledge Based Systems. In: Akman, V., Bouquet, P., Thomason, R., Young, R. (eds) Modeling and Using Context. CONTEXT 2001. Lecture Notes in Computer Science(), vol 2116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44607-9_45

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  • DOI: https://doi.org/10.1007/3-540-44607-9_45

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42379-9

  • Online ISBN: 978-3-540-44607-1

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