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Expertise in a Hybrid Diagnostic-Recommendation System for SMEs: A Successful Real-Life Application

Author

Listed:
  • Sylvain Delisle

    (INRPME - Institut de recherche sur les PME - UQTR - Université du Québec à Trois-Rivières, UQTR - Université du Québec à Trois-Rivières)

  • Josée St-Pierre

    (INRPME - Institut de recherche sur les PME - UQTR - Université du Québec à Trois-Rivières, UQTR - Université du Québec à Trois-Rivières)

Abstract

We describe a hybrid expert diagnosis-recommendation system we have developed for SMEs. The system is fully implemented and operational, and has been successfully put to use on data from actual SMEs. Although the system is packed with knowledge and expertise, it was not implemented with " traditional " symbolic AI techniques. We explain why and discuss how the system relates to expert systems, decision support systems, and AI. We also report on an experimental evaluation and identify ongoing and future developments.

Suggested Citation

  • Sylvain Delisle & Josée St-Pierre, 2004. "Expertise in a Hybrid Diagnostic-Recommendation System for SMEs: A Successful Real-Life Application," Post-Print hal-01704927, HAL.
    • Handle: RePEc:hal:journl:hal-01704927
    Note: View the original document on HAL open archive server: https://hal.science/hal-01704927
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    References listed on IDEAS

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    1. Price, D. H. R. & Beach, R. & Muhlemann, A. P. & Sharp, J. A. & Paterson, A., 1998. "A system to support the enhancement of strategic flexibility in manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 109(2), pages 362-376, September.
    2. Muhlemann, A. & Price, D. & Afferson, M. & Sharp, J., 1995. "A computer based approach for enhancing manufacturing decision making in smaller manufacturing enterprises: A longitudinal study," Omega, Elsevier, vol. 23(1), pages 97-107, February.
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    Cited by:

    1. Jean-François Beaudoin & Sylvain Delisle & Mathieu Dugré & Josée St-Pierre, 2005. "Reengineering the Knowledge Component of a Data Warehouse-based Expert Diagnosis System," Post-Print hal-01704902, HAL.

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