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Activating Case-Based Reasoning with Active Databases

  • Sheng Li
  • Qiang Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1898)

Abstract

Many of today’s CBR systems are passive in nature: they require human users to activate them manually and to provide information about the incoming problem explicitly. In this paper, we present an integrated system that combines CBR system with an active database system. Active databases, with the support of active rules, can perform event detecting, condition monitoring, and event handling (action execution) in an automatic manner. The combined ActiveCBR system consists of two layers. In the lower layer, the active database is rule-driven; in the higher layer, the result of action execution of active rules is transformed into feature-value pairs required by the CBR subsystem. The layered architecture separates case-based reasoning from complicated rule-based reasoning, and improves the traditional passive CBR system with the active property. This paper shows how to construct ActiveCBR system and provides an analysis of the resulting system architecture.

Keywords

Action Execution Active Rule Active Database Case Retrieval Rule Execution 
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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References

  1. 1.
    A. Aamodt and E. Plaza. Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications, 7(1):39–59, 1993.CrossRefGoogle Scholar
  2. 2.
    A. Biliris. The performance of three database storage structures for managing large objects. In ACM SIGMOD Conference on the Management of Data, San Diego, CA, 1992.Google Scholar
  3. 3.
    S. Ceri, P. Fraternali, S. Paraboschi, and L. Branca. Active rule management in Chimera. In Active Database Systems-Triggers and Rules For Advanced Database Processing, pages 151–76. Morgan Kaufman, 1996.Google Scholar
  4. 4.
    O. Diaz and A. Jaime. EXACT: an extensible approach to active object-oriented databases. VLDB Journal, 6(4):282–295, 1997.CrossRefGoogle Scholar
  5. 5.
    O. Diaz, A. Jaime, N. W. Paton, and G. Qaimari. Supporting dynamic displays using active rules. A CM SIGMOD Record, 23(1):21–26, 1994.CrossRefGoogle Scholar
  6. 6.
    D. Gentner. Structure mapping: a theoretical framework for analogy. Cognitive Science, 7:155–70, 1983.CrossRefGoogle Scholar
  7. 7.
    J. L. Kolodner. Case-Based Reasoning. Morgan Kaufmann Publisers, Inc., 1993.Google Scholar
  8. 8.
    D. B. Leake, A. Kinley, and D. Wilson. Learning to improve case adaptation by introspective reasoning and CBR. In Proceedings of the First International Conference on Case-Based Reasoning. Springer-Verlag, 1995.Google Scholar
  9. 9.
    K. Owens and S. Adams. Oracle 7 triggers: Mutating tables? Database Programming and Design, 7(10):31–49, 1994.Google Scholar
  10. 10.
    J. Quinlan. Induction of decision trees. Machine Learning, 1:81–106, 1986.Google Scholar
  11. 11.
    Y. Shoham. An overview of agent-oriented programming. In J.M. Bradshaw, editor, Software Agents, pages 271–90. AAAI Press, 1997.Google Scholar
  12. 12.
    I. Watson and F. Marir. Case-based reasoning: A review. The Knowledge Engineering Review, 9(4):355–81, 1994.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Sheng Li
    • 1
  • Qiang Yang
    • 1
  1. 1.School of Computing ScienceSimon Fraser UniversityBurnabyCanada

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