Using naturally occurring texts as a knowledge acquisition resource for knowledge base design: developing a knowledge base taxonomy on microprocessors
<p>Many artificial intelligence applications suffer severely from a bottleneck in acquiring domain information necessary to go beyond toy hand-built demonstrations to realistic applications. This project examines one approach to reducing that bottleneck by using automated and semi-automated te...
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| Format: | Dissertation |
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Virginia Tech
2014
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| Online Access: | http://hdl.handle.net/10919/41162 http://scholar.lib.vt.edu/theses/available/etd-02162010-020204/ |
| Summary: | <p>Many artificial intelligence applications suffer severely from a
bottleneck in acquiring domain information necessary to go beyond toy
hand-built demonstrations to realistic applications. This project
examines one approach to reducing that bottleneck by using automated and
semi-automated techniques to analyze published domain-relevant material.
A taxonomy of terms related to computers with an emphasis on
microprocessors is developed and presented. The methods used are
experimental and not yet fully validated, but are potentially of great
use for extracting useful domain information from published material.
Preliminary validation by comparison with a published taxonomy shows
that these methods have produced a taxonomy which is better suited for
the immediate use of this taxonomy.</p> === Master of Science |
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