Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
PAKM '02 Proceedings of the 4th International Conference on Practical Aspects of Knowledge Management
Capturing Lessons Learned for Variation Reduction in an Automotive Assembly Plant
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
Applying Knowledge Management: Techniques for Building Corporate Memories
Applying Knowledge Management: Techniques for Building Corporate Memories
Compare&contrast: using the web to discover comparable cases for news stories
Proceedings of the 16th international conference on World Wide Web
Using domain knowledge for ontology-guided entity extraction from noisy, unstructured text data
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
The general motors variation-reduction adviser: deployment issues for an AI application
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Introduction strategy and feedback from an experience management project
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
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The GM Variation-Reduction Adviser (VRA) was originally conceived and prototyped as a CBR system. Feedback from the users led to a variety of changes in the system. It is emerging now as an application destined for all GM assembly plants. This is a fine "success story." However, the VRA has lost so much of its CBR character that it might be best characterized as a "CBR inspired" system rather than a CBR system. In this paper, we describe the original concept and the user feedback that guided its evolution into its current form. Every "real application" has interesting stories about "what worked" and "what didn't." Here, we share some of these stories about our project.