Knowledge Level Engineering Ontological Analysis
Abstract
Knowledge engineering suffers from a lack of formal tools for understanding domains of interest. Current practice relies on an intuitive, informal approach for collecting expert knowledge and formulating it into a representation scheme adequate for symbolic processing. Implicit in this process, the knowledge engineer formulates a model of the domain, and creates formal data structures (knowledge base) and procedures (inference engine) to solve the task at hand. Newell (1982) has proposed that there should be a knowledge level analysis to aid the development of AI systems in general and knowledge-based expert systems in particular. This paper describes a methodology, called ontological analysis, which provides this level of analysis. The methodology consists of an analysis tool and its principles of use that result in a formal specification of the knowledge elements in a task domain.
Cite
Text
Alexander et al. "Knowledge Level Engineering Ontological Analysis." AAAI Conference on Artificial Intelligence, 1986.Markdown
[Alexander et al. "Knowledge Level Engineering Ontological Analysis." AAAI Conference on Artificial Intelligence, 1986.](https://mlanthology.org/aaai/1986/alexander1986aaai-knowledge/)BibTeX
@inproceedings{alexander1986aaai-knowledge,
title = {{Knowledge Level Engineering Ontological Analysis}},
author = {Alexander, James H. and Freiling, Michael J. and Shulman, Sheryl and Staley, Jeffery and Rehfuss, Steven and Messick, Steven},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1986},
pages = {963-968},
url = {https://mlanthology.org/aaai/1986/alexander1986aaai-knowledge/}
}