SALT: a knowledge acquisition language for propose-and-revise systems
Artificial Intelligence
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IEEE Expert: Intelligent Systems and Their Applications
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Expert Systems with Applications: An International Journal
KAMET II: An open diagnosis knowledge-acquisition methodology
Journal of Computational Methods in Sciences and Engineering - Selected papers from the International Conference on Computer Science,Software Engineering, Information Technology, e-Business, and Applications, 2003
VODKA: Variant objects discovering knowledge acquisition
Expert Systems with Applications: An International Journal
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Expert Systems with Applications: An International Journal
Foundations of ontology-based MAS methodologies
AOIS'05 Proceedings of the 7th international conference on Agent-Oriented Information Systems III
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KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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The knowledge acquisition (KA) process is not ''mining from the expert's head'' and writing rules for building knowledge-based systems (KBS), as it was 20years ago when KA was often confused with knowledge elicitation activity, and modern engineering tools did not exist. The KA process has definitely changed. Today knowledge acquisition is considered a cognitive process that involves both dynamic modeling and knowledge generation activities. KA should be seen as a spiral of epistemological and ontological content that grows upward by transforming tacit knowledge into explicit knowledge, which in turn becomes the basis for a new spiral of knowledge generation. This paper presents some of our attempts to build a new knowledge acquisition methodology that brings together and includes all of these ideas. KAMET II, the evolution of KAMET (Cairo, 1998), represents a modern approach to creating diagnosis-specialized knowledge models that can be run by Protege 2000, the open source ontology editor and knowledge-based framework.