Design for acquisition: principles of knowledge-system design to facilitate knowledge acquisition
International Journal of Man-Machine Studies - Knowledge acquisition for knowledge-based systems. Part 2
Acquiring strategic knowledge from experts
International Journal of Man-Machine Studies
Automated Knowledge Acquisition for Strategic Knowledge
Machine Learning
Use of meta level knowledge in the construction and maintenance of large knowledge bases.
Use of meta level knowledge in the construction and maintenance of large knowledge bases.
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Database design with common sense business reasoning and learning
ACM Transactions on Database Systems (TODS)
Causal Knowledge Elicitation Based on Elicitation Failures
IEEE Transactions on Knowledge and Data Engineering
Strategic Reasoning Under Trade-Offs between Action Costs and Advantages
IEEE Transactions on Knowledge and Data Engineering
Naive Semantics to Support Automated Database Design
IEEE Transactions on Knowledge and Data Engineering
A Methodology for Learning Across Application Domains for Database Design Systems
IEEE Transactions on Knowledge and Data Engineering
Meta-analysis for Validation and Strategic Planning
RuleML '08 Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web
An intelligent system for monitoring and diagnosis of the CO2 capture process
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Strategic common sense is defined as the heuristic considerations human experts often apply to decide which choice is the most opportune to make from a set of possible alternatives. A method for acquiring modeling, and representing human strategic common sense in diagnostic expert systems is presented. The preference parameter and preference criterion tools, which are used to define a basic level of strategic knowledge, are reviewed. Strategic common sense and its representation using general rules and metarules modeling are discussed. An interview with a physician who provided a medical case and the related solutions is summarized. It is shown that the solutions given by the physician match the conclusions obtained by applying the strategic common sense rules to the medical example.