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Refining conversational case libraries

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Case-Based Reasoning Research and Development (ICCBR 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1266))

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Abstract

Conversational case-based reasoning (CBR) shells (e.g., Inference's CBR Express) are commercially successful tools for supporting the development of help desk and related applications. In contrast to rule-based expert systems, they capture knowledge as cases rather than more problematic rules, and they can be incrementally extended. However, rather than eliminate the knowledge engineering bottleneck, they refocus it on case engineering, the task of carefully authoring cases according to library design guidelines to ensure good performance. Designing complex libraries according to these guidelines is difficult; software is needed to assist users with case authoring. We describe an approach for revising case libraries according to design guidelines, its implementation in Clire, and empirical results showing that, under some conditions, this approach can improve conversational CBR performance.

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References

  • Auriol, E., Wess. S., Manago, M., Althoff, K.-D., & Traphöner, R. (1995). Inreca: A seamlessly integrated system based on inductive inference and case-based reasoning. Proceedings of the First ICCBR (pp. 371–380). Sesimbra, Portugal: Springer.

    Google Scholar 

  • Breslow, L., & Aha, D. W. (1997). Simplifying decision trees: A survey. To appear in Knowledge Engineering Review.

    Google Scholar 

  • Cardie, C. (1993). Using decision trees to improve case-based learning. Proceedings of the Tenth ICML (pp. 25–32). Amherst, MA: Morgan Kaufmann.

    Google Scholar 

  • Domingos, P. (1997). Context-sensitive feature selection for lazy learners. Artificial Intelligence Review, 11, 227–253.

    Google Scholar 

  • Fox, S., & Leake, D. L. (1995). Using introspective reasoning to refine indexing. Proceedings of the Fourteenth IJCAI (pp. 391–397). Montreal: Morgan Kaufmann.

    Google Scholar 

  • Heider, R., Auriol, E., Tartarin, E., & Manago, M. (1997). Improving the quality of case bases for building better decision support systems. In R. Bergmann & W. Wilke (Eds.) Fifth German Workshop on CBR: Foundations, Systems, and Applications (Technical Report LSA-97-01E). University of Kaiserslautern, Department of Computer Science.

    Google Scholar 

  • Inference Corporation (1995). CBR2: Designing CBR Express Case Bases. Unpublished.

    Google Scholar 

  • Kitano H., Shimazu H., & Shibata A. (1993). Case-method: A methodology for building large-scale case-based systems. Proceedings of the Eleventh NCAI (pp. 303–308). Washington, DC: AAAI Press.

    Google Scholar 

  • Ku, S., & Suh, Y.-H. (1996). An investigation of the K-tree search algorithm for efficient case representation and retrieval. Expert Systems with Applications, 11, 571–581.

    Google Scholar 

  • Manago, M., Althoff, K.-D., Auriol, E., Traphoner, R., Wess, S., Conruyt, N., & Maurer, F. (1993). Induction and reasoning from cases. Proceedings of the First EWCBR (pp. 313–318). Kaiserslautern, Germany: Springer-Verlag.

    Google Scholar 

  • Nguyen, T., Czerwinsksi, M., & Lee, D. (1993). COMPAQ QuickSource: Providing the consumer with the power of artificial intelligence. Proceedings of the Fifth IAAI (pp. 142–150). Washington, DC: AAAI Press.

    Google Scholar 

  • Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1, 81–106.

    Google Scholar 

  • Quinlan, J. R. (1989). Unknown attribute values in induction. Proceedings of the Sixth IWML (pp. 164–168). Ithaca, NY: Morgan Kaufmann.

    Google Scholar 

  • Smyth, B., & Cunningham, P. (1994). A comparison of incremental CBR and inductive learning. In M. Keane, J. P. Haton, & M. Manago (Eds.) Working Papers of the Second EWCBR. Chantilly, France: Unpublished.

    Google Scholar 

  • Tan, M., & Schlimmer, J. C. (1990). Two case studies in cost-sensitive concept acquisition. Proceedings of the Eighth NCAI (pp. 854–860). Boston, MA: AAAI Press.

    Google Scholar 

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Authors and Affiliations

  1. Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory, 20375, Washington DC, USA

    David W. Aha & Leonard A. Breslow

Authors
  1. David W. Aha
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  2. Leonard A. Breslow
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David B. Leake Enric Plaza

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© 1997 Springer-Verlag Berlin Heidelberg

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Aha, D.W., Breslow, L.A. (1997). Refining conversational case libraries. In: Leake, D.B., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 1997. Lecture Notes in Computer Science, vol 1266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63233-6_498

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  • DOI: https://doi.org/10.1007/3-540-63233-6_498

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63233-7

  • Online ISBN: 978-3-540-69238-6

  • eBook Packages: Springer Book Archive

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