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Details

Ferrets and Topic Maps: Knowledge Engineering for an Analytical Engine.

DE2001782036

Publication Date	2001
Personal Author	Mason, J. D.
Page Count	26
Abstract	The 'Ferret' analytical engine, developed originally by the Y-12 National Security complex of the U.S. Department of Energy to seek classified data and associations in documents and present its findings in the light of formal rules, requires a structured information base that represents not just individual facts but a set of implications and a collection of rules. The fundamental knowledge base is evolving towards forms that enhance flexibility and portability. The developers early realized that the knowledge base can be captured in XML by a series of trees that represent taxonomies, analytical structures, and specific indicative facts, but over this a topic map is needed to express links across the trees. Above this, the classification rules could form another topic map that points into the lower layers. In its latest form, however, the knowledge base has come to entirely represented in a topic map.
Keywords	Artificial intelligence Computer programs Data collection Classification rules Systems engineering Ferrets Topic maps Knowledge based systems Analytical engines
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Y-12 National Security Complex, Oak Ridge, TN.; Science Applications International Corp., McLean, VA.
Supplemental Notes	Prepared in cooperation with Science Applications International Corp., McLean, VA.
Document Type	Technical Report
NTIS Issue Number	200123

Ferrets and Topic Maps: Knowledge Engineering for an Analytical Engine.

Ferrets and Topic Maps: Knowledge Engineering for an Analytical Engine.
DE2001782036

Publication Date	2001
Personal Author	Mason, J. D.
Page Count	26
Abstract	The 'Ferret' analytical engine, developed originally by the Y-12 National Security complex of the U.S. Department of Energy to seek classified data and associations in documents and present its findings in the light of formal rules, requires a structured information base that represents not just individual facts but a set of implications and a collection of rules. The fundamental knowledge base is evolving towards forms that enhance flexibility and portability. The developers early realized that the knowledge base can be captured in XML by a series of trees that represent taxonomies, analytical structures, and specific indicative facts, but over this a topic map is needed to express links across the trees. Above this, the classification rules could form another topic map that points into the lower layers. In its latest form, however, the knowledge base has come to entirely represented in a topic map.
Keywords	Artificial intelligence Computer programs Data collection Classification rules Systems engineering Ferrets Topic maps Knowledge based systems Analytical engines
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Y-12 National Security Complex, Oak Ridge, TN.; Science Applications International Corp., McLean, VA.
Supplemental Notes	Prepared in cooperation with Science Applications International Corp., McLean, VA.
Document Type	Technical Report
NTIS Issue Number	200123