Comparison of conceptual graphs for modelling knowledge of multiple experts

  • Rose Dieng
Communications Session 1A Knowledge Representation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1079)


When modeling expertise from multiple experts, expertise conflicts among the expertise models of the different experts must be tackled, so as to build their common expertise model. The domain level of an expertise model can be represented using Sowa's conceptual graph formalism. This paper presents a method for conflict management during knowledge modeling from multiple experts: this method is based on the comparison and integration of multiple conceptual graphs corresponding to different viewpoints, the integration being guided by different integration strategies.


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  1. 1.
    M. Chein, and M. L. Mugnier. Conceptual Graphs: Fundamental Notions. RIA, 6(4):365–406,1992.Google Scholar
  2. 2.
    O. Cogis, and O. Guinaldo. A Linear Descriptor for Conceptual Graphs and a Class for Polynomial Isomorphism Test. In G. Ellis et al, eds, Conceptual Structures: Applications, Implementation and Theory, Springer-Verlag, LNAI 954, pp. 263–277, Santa Cruz, CA, Aug. 1995.Google Scholar
  3. 3.
    R. Dieng. Conflict Management in Knowledge Acquisition. In I. Smith (Ed), AIEDAM, Special Issue on Conflict Management in Design, 9(4):337–351 September 1995.Google Scholar
  4. 4.
    R. Dieng, O. Corby, and S. Labidi. Expertise Conflicts in Knowledge Acquisition. In B. Gaines, and M. Musen, eds, Proc. of KAW-94, pp. 23-1–23-20, Banff, Canada, Jan.–Feb. 1994.Google Scholar
  5. 5.
    R. Dieng, O. Corby, and S. Labidi. Agent-Based Knowledge Acquisition. In L. Steels et al, eds A Future for Knowledge Acquisition: EKAW'94, Springer-Verlag, LNAI 867, pp. 63–82, Sept. 1994.Google Scholar
  6. 6.
    R. Dieng. Comparison of Conceptual Graphs for Modelling Knowledge of Multiple Experts. INRIA Research Report, February 1996.Google Scholar
  7. 7.
    S. Easterbrook. Handling conflict between domain descriptions with computer-supported negotiation. Knowledge Acquisition, 3(3):255–289, September 1991.Google Scholar
  8. 8.
    S. M. Easterbrook. Distributed Knowledge Acquisition as a Model for Requirements Elicitation. In Proc. of EKAW-89, pp. 530–543, Paris, France, July 1989.Google Scholar
  9. 9.
    J. Eggen, A. M. Lundteigen., and M. Mehus. Integration of Knowledge from Different Knowledge Acquisition Tools. In B. Wielinga et al. eds, Proc. of EKAW-90, Amsterdam, Feb. 1990. IOS Press.Google Scholar
  10. 10.
    B. R. Gaines, and M. L. G. Shaw Comparing the Conceptual Systems of Experts. In Proceedings of the 9th IJCAI (IJCAI-89), pp. 633–638, Detroit, 1989.Google Scholar
  11. 11.
    C. Garcia. Construction coopérative d'ontologies dans un cadre de multi-expertise. Rapport de stage de DEA Informatique, LIRMM, Montpellier, September 1995.Google Scholar
  12. 12.
    M. M. Kayaalp and J. R. Sullins Multifaceted Ontological Networks: Reorganization and Representation of Knowledge in Natural Sciences. In Proc. of KAW-94, pp. 25-1–25-19, Banff, Canada, Jan.–Feb. 1994.Google Scholar
  13. 13.
    M. Klein. Detecting and resolving conflicts among cooperating human and machine-based design agents. Artificial Intelligence in Engineering, 7:93–104, 1992Google Scholar
  14. 14.
    G. W. Mineau, and M. Allouche. Establishing a Semantic Basis: Toward the Integration of Vocabularies. In Gaines et al eds Proc. of KAW'95, pp. 2-1–2-16, Banff, Canada, Feb. 1995.Google Scholar
  15. 15.
    K. S. Murray, and B. W. Porter. Developing a tool for knowledge integration: initial results. International Journal of Man-Machine Studies, 33:373–383, 1990.Google Scholar
  16. 16.
    A. Newell. The knowledge level. Artificial Intelligence, 18:87–127, 1982.Google Scholar
  17. 17.
    J. Poole, and J. A. Campbell. A Novel Algorithm for Matching Conceptual and Related Graphs. In G. Ellis et al eds, Conceptual Structures: Applications, Implementation and Theory, pp. 293–307, Santa Cruz, CA, USA, August 1995. Springer-Verlag, LNAI 954.Google Scholar
  18. 18.
    M. Ribière, R. Dieng, M. Fornarino, A.-M. Pinna-Dery. Intégration d'un formalisme de liens dans le formalisme des graphes conceptuels. INRIA Research Report, February 1996.Google Scholar
  19. 19.
    M. L. G. Shaw, and B. R. Gaines. A methodology for recognizing conflict, correspondence, consensus and contrast in a knowledge acquisition system. Knowledge Acqu., 1(4):341–363, Dec. 1989.Google Scholar
  20. 20.
    J. F. Sowa. Conceptual Structures: Information Processing in Mind and Machine. Reading, Addison-Wesley, 1984.Google Scholar
  21. 21.
    J.F. Sowa. Conceptual Graphs Summary. In T.E. Nagle et al, eds Conceptual Structures: Current Research and Practice, England, Ellis Horwood Workshops, 1992.Google Scholar
  22. 22.
    J.F. Sowa. Relating Diagrams to Logic. In Proc of ICCS'93, Québec City, Canada, August 1993.Google Scholar
  23. 23.
    G. Wiederhold. Interoperation, Mediation and Ontologies. Proc. of FGCS'94 Workshop on Heterogeneous Cooperative Knowledge Bases, Tokyo, Japan, pp. 33–48, Dec. 1994.Google Scholar
  24. 24.
    B. Wielinga, G. Schreiber, and J. Breuker. KADS: a modelling approach to knowledge engineering. Knowledge Acquisition, 4:5–53, 1992.Google Scholar
  25. 25.
    M. Willems. Projection and Unification for Conceptual Graphs. In Ellis et al eds, Conceptual Structures: Applications, Implementation and Theory, pp. 278–292, Santa Cruz, Aug. 1995. Spring.-Verl., LNAI 954.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Rose Dieng
    • 1
  1. 1.ACACIA ProjectINRIASophia-Antipolis CedexFrance

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