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

Sylvain Delisle and Josée St-Pierre (josee.st-pierre@uqtr.ca)
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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

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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.

Date: 2004
Note: View the original document on HAL open archive server: https://hal.science/hal-01704927
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Published in 17th International Conference on Industrial et Engineering Applications of Artificial Intelligence (IEA/AIE), 2004, Ottawa, Canada

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