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Definition of a General Conceptualization Method for the Expert Knowledge

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Book cover MICAI 2000: Advances in Artificial Intelligence (MICAI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1793))

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Abstract

The community of knowledge engineers usually accepts the importance of the analysis process of the expert knowledge. This analysis, also known as conceptualization, is carried out at the knowledge level. The objective of this analysis is to obtain a conceptual model, from the knowledge acquired from the expert. The conceptual model collects the relevant parts of the reality for the problem solution, forgetting those elements that are not meaningful for the system. Furthermore, it permits that the knowledge engineer (KE) to understand the problem domain and to detect knowledge gaps or wrong interpretations. There are several proposals to accomplish this analysis at knowledge level, but they do not offer a detailed process that helps in the elaboration of the conceptual model. This work proposes a method to guide in the elaboration of the conceptual model.

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References

  1. Ageenko, I.I.: SIGART Bulletin Book Reviews 9(1), p. 345-347. Review of Fensel D.: The Knowledge Acquisition and Representation Language, KARL. Kluwer, Dordrecht (1995)

    Google Scholar 

  2. Angele, J., Fensel, D., Studer, R.: Domain and Task Modelling in MIKE. In: Proceedings of the IFIP WG 8.1/13.2 Joint Working Conference, Domain Knowledge for Interactive System Design, Geneva, Switzerland, May 8-10 (1996)

    Google Scholar 

  3. Bylander, T., Chandrasekaran, B.: Generic tasks for knowledge-based reasoning: the ”right” level of abstraction for knowledge acquisition. International Journal on Man-Machine Studies 26, 231–243 (1987)

    Article  Google Scholar 

  4. Chandrasekaran, B.: Towards a Taxonomy of Problem Solving Types. AI Magazine 4(1), 9–17 (1983)

    Google Scholar 

  5. Chandrasekaran, B.: Generic Task in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Desing. IEEE Expert 1(3), 23–30 (1986)

    Article  Google Scholar 

  6. Chandrasekaran, B.: Towards a Functional Architecture for Intelligence Based on Generic Information Processing Tasks. In: Proceedings IJCAI, pp. 1183–1192. Morgan Kaufmann, San Francisco (1987)

    Google Scholar 

  7. Chandrasekaran, B.: Design Problem Solving: A Task Analysis. AI Magazine 11(4), 59–71 (1990)

    Google Scholar 

  8. Chandrasekaran, B., Johnson, T.R., y Smith, J.W.: Task-Structure Analysis for Knowledge Modeling. Communications of the ACM 35(9), 124–137 (1992)

    Article  Google Scholar 

  9. Clancey, W.J.: Heuristic Classification. Artificial Intelligence 27, 289–350 (1985)

    Article  Google Scholar 

  10. Gómez, A., Juristo, N., Montes, C., Pazos, J.: Ingeniería del conocimiento, Centro de Estudios Ramón Areces S. A., Madrid (1997)

    Google Scholar 

  11. Gómez, A., Moreno, A., Pazos, J., Sierra-Alonso, A.: Knowledge maps: an essential technique for conceptualization, To appear in Data & Knowledge Engineering

    Google Scholar 

  12. McDermott, J.: Preliminary Steps Towards a Taxonomy of Problem-Solving Methods. In: Marcus, S. (ed.) Automating Knowledge Acquisitiopn for Expert Systems, pp. 225–266. Kluwer, Dordrecht (1988)

    Google Scholar 

  13. Molina, M., Gómez, A., Sierra, J.L.: Reusable Components for Building Conventional and Knowledge-based Systems: The KSM Approach. In: Proc. of the 9th International Conference on Software Engineering & Knowledge Engineering SEKE 1997, Madrid, pp. 168–176 (1997)

    Google Scholar 

  14. Newell, A.: The Knowledge Level. Artificial Intelligence 18(1), 87–127 (1982)

    Article  Google Scholar 

  15. Puerta, A.R., Tu, S.W., Musen, M.A.: Modeling tasks with mechanisms. International Journal of Intelligent Systems 8(1), 129–152 (1993)

    Article  Google Scholar 

  16. Rumbaugh, J., Jacobson, I., Booch, G.: The Unified Modelling Languaje Reference Manual. Addison-Wesley, Reading (1999)

    Google Scholar 

  17. Schreiber, G., Wielinga, B., Breuker, J. (eds.): KADS: A Principled Approach to Knowledge-Based System Developement. Academic Press, London (1993)

    Google Scholar 

  18. Sierra-Alonso, A.: Lenguaje y proceso para construcción de modelos conceptuales expertos. PhD Dissertation, Facultad de Informática, U. Politécnica de Madrid. To defend in (2000)

    Google Scholar 

  19. Steels, L.: Components of Expertise. AI Magazine 4(1), 28–49 (1990)

    Google Scholar 

  20. Studer, R., Benjamins, V.R., Fensel, D.: Knowledge Engineering: Principles and Methods. Data & Knowledge Engineering 25(1-2), 161–197 (1998)

    Article  MATH  Google Scholar 

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Sierra-Alonso, A. (2000). Definition of a General Conceptualization Method for the Expert Knowledge. In: Cairó, O., Sucar, L.E., Cantu, F.J. (eds) MICAI 2000: Advances in Artificial Intelligence. MICAI 2000. Lecture Notes in Computer Science(), vol 1793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720076_42

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  • DOI: https://doi.org/10.1007/10720076_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67354-5

  • Online ISBN: 978-3-540-45562-2

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