Graph-based Acquisition of Expressive Knowledge
by Chaudhri, V and Murray, K and Pacheco, J and Clark, P and Porter, B and Hayes, P
EKAW , 2004.
Capturing and exploiting knowledge is at the heart of several important problems such as decision-making, the semantic web, and intelligent agents. The captured knowledge must be accessible to sub-ject matter experts so that the knowledge can be easily extended, queried, and debugged. In our pre-vious work to meet this objective, we created a knowledge-authoring system based on graphical assembly from components that allowed acquisition of an interestingly broad class of axioms. In this paper, we explore the question: can we expand the axiom classes acquired by building on our existing graphical methods and still retain simplicity so that people with minimal training in knowledge repre-sentation can use it? Specifically, we present tech-niques used to capture ternary relations, classifica-tion rules, constraints, and if-then rules.
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| Name | Title | ||
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| Chaudhri, Vinay K | Program Director |  |
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Clark, Peter E. | Computer Scientist, Boeing | |
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Hayes, Pat | Senior Research Scientist, Univ of West Florida | |
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Murray, Kenneth S | Senior Computer Scientist | |
| Pacheco, John | Research Engineer | |
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Porter, Bruce | Professor, University of Texas at Austin | |
