Ontology-Driven Development of Conversational CBR Systems

  • Hector Gómez-Gauchía
  • Belén Díaz-Agudo
  • Pedro González-Calero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4106)


Conversational CBR has been used successfully for several years but building a new system demands a great cognitive effort of knowledge engineers and using it demands a similar effort of users. In this paper we use ontologies as the driving force to structure a development methodology where previous design efforts may be reused. We review the main issues of current CCBR models and their specific solutions. We describe afterwards how these solutions may be integrated in a common methodology to be reused in other similar CCBR systems. We particularly focus on the authoring issues to represent the knowledge.


Description Logic Case Model Knowledge Engineer Apply Intelligence Question Model 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aamodt, A.: Knowledge-intensive case-based reasoning in creek. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 1–15. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications 7(1) (1994)Google Scholar
  3. 3.
    Aha, D.W., Breslow, L.A., Muñoz-Avila, H.: Conversational case-based reasoning. Applied Intelligence 14(1), 9–32 (2001)zbMATHCrossRefGoogle Scholar
  4. 4.
    Aha, D.W., Maney, T., Breslow, L.: Supporting dialogue inferencing in conversational case-based reasoning. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 262–273. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  5. 5.
    Arcos, J.L., Mántaras, R.L.D.: An interactive case-based reasoning approach for generating expressive music. Applied Intelligence 14(1), 115–129 (2001)zbMATHCrossRefGoogle Scholar
  6. 6.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The description logic handbook: theory, implementation, and applications. Cambridge University Press, New York (2003)zbMATHGoogle Scholar
  7. 7.
    Díaz-Agudo, B., González-Calero, P.A.: CBROnto: a task/method ontology for CBR. In: Haller, S., Simmons, G. (eds.) Procs. of the 15th International FLAIRS 2002 Conference (Special Track on CBR), pp. 101–106. AAAI Press, Menlo Park (2002)Google Scholar
  8. 8.
    Fernández-López, M., Gómez-Pérez, A.: Overview and analysis of methodologies for building ontologies. Knowl. Eng. Rev. 17(2), 129–156 (2002)CrossRefGoogle Scholar
  9. 9.
    Göker, M., Thompson, C.: Personalized conversational case-based recommendation. In: Blanzieri, E., Portinale, L. (eds.) EWCBR 2000. LNCS (LNAI), vol. 1898. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  10. 10.
    Göker, M.H.: Adapting to the level of experience of the user in mixed-initiative web self-service applications. In: Aha, D. (ed.) Proceedings, Workshop on Mixed Initiative Case-Based Reasoning, at the 5th International Conference on Case Based Reasoning, ICCBR, Trondheim, Norway, June 23-26 (2003)Google Scholar
  11. 11.
    Gómez-Gauchía, H., Díaz-Agudo, B., Gómez-Martín, P.P., González-Calero, P.A.: Supporting conversation variability in cobber using causal loops. In: Muñoz-Ávila, H., Ricci, F. (eds.) [25], 252–266 (2005)CrossRefGoogle Scholar
  12. 12.
    Gómez-Gauchía, H., Díaz-Agudo, B., González-Calero, P.A.: A pragmatic methodology for conceptualization with two layered knowledge representation: a case study. In: Pfeiffer, H., Wolf, K., Delugach, H. (eds.) Contributions to ICCS 2004. 12th International Conference on Conceptual Structures, ICCS 2004, December 20-22, 2004. Shaker Verlag (2004)Google Scholar
  13. 13.
    Gómez-Gauchía, H., Díaz-Agudo, B., González-Calero, P.A.: Cobber, toward an affective conversational ki-cbr framework. In: Prasad, B. (ed.) Procs of the 2nd Indian International Conference on Artificial Intelligence IICAI 2005, Pune, India, December 20-22, 2005, pp. 1804–1820 (2005)Google Scholar
  14. 14.
    Gómez-Gauchía, H., Díaz-Agudo, B., González-Calero, P.A.: Automatic personalization of the human computer interaction using temperaments. In: Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2006, Melbourne Beach, Florida, USA, May 11-13, 2006. AAAI Press, Menlo Park (2006)Google Scholar
  15. 15.
    Gomez-Perez, A., Corcho-Garcia, O., Fernandez-Lopez, M.: Ontological Engineering. Springer, New York (2003)Google Scholar
  16. 16.
    Gu, M., Aamodt, A.: A knowledge-intensive method for conversational cbr. In: Muñoz-Ávila, H., Ricci, F. (eds.) [25], pp.296–311 (2005)CrossRefGoogle Scholar
  17. 17.
    Guin-Duclosson, N., Jean-Daubias, S., Nogry, S.: The ambre ile: How to use case-based reasoning to teach methods. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 782–791. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  18. 18.
    Gupta, K.M., Aha, D.W.: A framework for incremental query formulation in mixed-initiative case-based reasoning. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689. Springer, Heidelberg (2003)Google Scholar
  19. 19.
    Knublauch, H.: User-defined datatypes in protege-owl (2005),
  20. 20.
    Leake, D.B., Wilson, D.C.: A case-based framework for interactive capture and reuse of design knowledge. Applied Intelligence 14(1), 77–94 (2001)zbMATHCrossRefGoogle Scholar
  21. 21.
    Mckenna, E., Smyth, B.: An interactive visualisation tool for case-based reasoners. Applied Intelligence 14(1), 95–114 (2001)zbMATHCrossRefGoogle Scholar
  22. 22.
    McSherry, D.: Interactive case-based reasoning in sequential diagnosis. Applied Intelligence 14(1), 65–76 (2001)zbMATHCrossRefGoogle Scholar
  23. 23.
    Mehmet, G.C.F., Aktas, S., Pierce, M., Leake, D.: A web based conversational case-based recommender system for ontology aided metadata discovery. In: Fifth IEEE/ACM International Workshop on Grid Computing (GRID 2004), pp. 69–75 (2004)Google Scholar
  24. 24.
    Muñoz-Avila, H., Aha, D.W., Breslow, L., Nau, D.: HICAP: an interactive case-based planning architecture and its application to noncombat evacuation operations. In: AAAI 1999/IAAI 1999: Procs of the sixteenth national conference on Artificial Intelligence, pp. 870–875. AAAI, Menlo Park (1999)Google Scholar
  25. 25.
    Muñoz-Ávila, H., Ricci, F. (eds.): ICCBR 2005. LNCS (LNAI), vol. 3620. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  26. 26.
    Recio, J.A., Díaz-Agudo, B., Gǿmez-Martín, M.A.: Extending jCOLIBRI for textual CBR. In: Muñoz-Ávila, H., Ricci, F. (eds.) [25], pp.421–435 (2005)CrossRefGoogle Scholar
  27. 27.
    Reilly, J., McCarthy, K., McGinty, L., Smyth, B.: Explaining compound critiques. Artif. Intell. Rev. 24(2), 199–220 (2005)CrossRefGoogle Scholar
  28. 28.
    Simazu, H., Shibata, A., Nihei, K.: Expertguide: A conversational case-based reasoning tool for developing mentors in knowledge spaces. Applied Intelligence 14(1), 33–48 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hector Gómez-Gauchía
    • 1
  • Belén Díaz-Agudo
    • 1
  • Pedro González-Calero
    • 1
  1. 1.Dep. Sistemas Informáticos y ProgramaciónUniversidad Complutense de MadridSpain

Personalised recommendations