| Cavazza and Zweigenbaum, 1994. Semantic Analysis and In-Depth Understanding of Technical Texts. Applied Artificial Intelligence, vol. 8, n. 4. |
....to induction as described in [Holland et al. 1986] and the technical solutions provided by various AI techniques. In a former study of datadriven approaches to induction, we introduced the notion of dual concepts , to relate textual descriptions to qualitative simulations of physical processes [Cavazza Zweigenbaum, 1994]. Such an approach involved building a symbolic world model 3 from a textual description and being able to redescribe it in natural language as it evolves as a consequence of the spontaneous behaviours of its constituent objects. A dual concept is thus the association, under the same conceptual ....
....topdown approach, the system actively seeks instances of specific application concepts by applying recognition rules to world objects for each concept to be recognised. In a bottom up approach, datadriven procedures will trigger the recognition of high level concepts by reacting to object changes [Cavazza Zweigenbaum, 1994]. Both approaches have to rely on efficient pattern matching algorithms to determine meaningful object configurations. The fact that interpretation targets a finite set of high level concepts would be in favour of a top down approach, which could be further optimised by only considering those ....
Cavazza and Zweigenbaum, 1994. Semantic Analysis and In-Depth Understanding of Technical Texts. Applied Artificial Intelligence, vol. 8, n. 4.
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Marc Cavazza and Pierre Zweigenbaum Rapport Interne RI-86 Accepted for publication in Applied Artificial Intelligence. Semantic Analysis and In-Depth Understanding of Technical Texts 27/27 Johnson-Laird, P. N., 1983. Mental Models. Cambridge: Cambridge University Press.
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