Abstract
Relational databases are in widespread use, yet they suffer from serious limitations when one uses them for reasoning about real-world enterprises. This is due to the fact that database relations possess no inherent semantics. This paper describes an approach called microanalysis that we have used to effectively capture database semantics represented by conceptual graphs. The technique prescribes a manual knowledge acquisition process whereby each relation schema is captured in a single conceptual graph. The schema's graph can then easily be instantiated for each tuple in the database forming a set of graphs representing the entire database's semantics. Although our technique originally was developed to capture semantics in a restricted domain of interest, namely database inference detection, we believe that domain-directed microanalysis is a general approach that can be of significant value for databases in many domains. We describe the approach and give a brief example.
This work was supported under U.S. Department of Defense, Maryland Procurement Office Contract No. MDA904-92-C-5146.
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Delugach, H.S., Hinke, T.H. (1996). Microanalysis: Acquiring database semantics in conceptual graphs. In: Eklund, P.W., Ellis, G., Mann, G. (eds) Conceptual Structures: Knowledge Representation as Interlingua. ICCS 1996. Lecture Notes in Computer Science, vol 1115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61534-2_14
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DOI: https://doi.org/10.1007/3-540-61534-2_14
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