CBR Outcome Evaluation for High Similar Cases: A Preliminary Approach

  • José M. Juarez
  • Manuel Campos
  • Antonio Gomariz
  • José T. Palma
  • Roque Marín
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5988)

Abstract

Case-based reasoning has demonstrated to be a suitable similarity-based approach to develop decision-support system in different domains. However, in certain scenarios CBR finds difficulties to obtain a reliable solution when retrieved cases are highly similar. For example, patients from an Intensive Care Unit are critical patients in which slight variations of monitored parameters have a deep impact on the patient severity evaluation. In this scenario, it seems necessary to extend the system outcome in order to indicate the reliance of the solution obtained. Main efforts in the literature for CBR evaluation focus on case retrieval (i.e. similarity) or a retrospective analysis. However, these approaches do not seem to suffice when cases are very close. To this end, we propose three techniques to obtain a reliance solution degree, one based on case retrieval and two based on case adaptation. We also show the capacities of this proposal in a medical problem.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications 7(1), 39–59 (1994)Google Scholar
  2. 2.
    Aha, D.W., Breslow, L.A.: Refining conversational case libraries. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266, pp. 267–278. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  3. 3.
    Bogaerts, S., Leake, D.B.: What evaluation criteria are right for CCBR? considering rank quality. In: Roth-Berghofer, T.R., Göker, M.H., Güvenir, H.A. (eds.) ECCBR 2006. LNCS (LNAI), vol. 4106, pp. 385–399. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Gupta, K.M., Aha, D.W., Sandhu, N.: Exploiting taxonomic and causal relations in conversational case retrieval. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 133–147. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Huellermeier, E.: Case-Based Approximate Reasoning. Springer, New York (2007)Google Scholar
  6. 6.
    Juárez, J.M., Campos, M., Palma, J., Marín, R.: Computing context-dependent temporal diagnosis in complex domains. Expert Systems with Applications 35(3), 991–1010 (2007)CrossRefGoogle Scholar
  7. 7.
    Klir, G.J., Folger, T.A.: Fuzzy Sets, Uncertainty, and Information. Prentice-Hall, N.J. (1992)MATHGoogle Scholar
  8. 8.
    Kohlmaier, A., Schmitt, S., Bergmann, R.: Evaluation of a similarity-based approach to customer-adaptive electronic sales dialogs. In: Empirical Evaluation of Adaptive Systems. Proceedings of the workshop held at the 8th International Conference on User Modelling, pp. 40–50 (2001)Google Scholar
  9. 9.
    Kolodner, J.L., Leake, D.B.: A Tutorial Introduction to Case-Based Reasoning, ch. 2, pp. 31–65. American Association for Artificial Intelligence (1996)Google Scholar
  10. 10.
    Koton, P.: Using experience in learning and problem solving. Technical Report, MIT/LCS/TR-441 (1989)Google Scholar
  11. 11.
    Leake, D.B.: CBR in Context: The Present and The Future, ch. 1, pp. 31–65. American Association for Artificial Intelligence (1996)Google Scholar
  12. 12.
    Palma, J., Juárez, J.M., Campos, M., Marín, R.: A fuzzy theory approach for temporal model-based diagnosis. Artificial Intelligence in Medicine 38, 197–218 (2006)CrossRefGoogle Scholar
  13. 13.
    Watson, I.: Case-based reasoning is a methodology not a technology. Knowledge-Based Systems 12, 303–308 (1999)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • José M. Juarez
    • 1
  • Manuel Campos
    • 2
  • Antonio Gomariz
    • 1
  • José T. Palma
    • 1
  • Roque Marín
    • 1
  1. 1.Information and Communication Engineering DepartmentUniversity of MurciaSpain
  2. 2.Computer Science and Systems DepartmentUniversity of MurciaSpain

Personalised recommendations