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An overview of Knowledge Representation
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Source International Conference on Management of Data archive
Proceedings of the 1980 workshop on Data abstraction, databases and conceptual modeling table of contents
Pingree Park, Colorado, United States
Pages: 5 - 12  
Year of Publication: 1980
ISBN:0-89791-031-1
Also published in ...
Author
John Mylopoulos  Department of Computer Science, University of Toronto
Sponsors
NBS : National Bureau of Standards
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

This is a brief overview of terminology and issues related to Knowledge Representation (here-after KR) research, intended primarily for researchers working on Semantic Data Models within Database Management and Program Specifications within Programming Languages/Software Engineering. Knowledge Representation is a central problem in Artificial Intelligence (AI) today. Its importance stems from the fact that the current design paradigm for “intelligent” systems stresses the need for expert knowledge in the system along with associated knowledge-handling facilities. This paradigm is in sharp contrast to earlier ones which might be termed “power-oriented” [Goldstein and Papert 77] in that they placed an emphasis on general purpose heuristic search techniques [Nilsson 71].


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  8