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This paper presents graph operations for processing conceptual graph rules in forward chaining and backward chaining. In both cases the operations provide sound and complete procedures with respect to rst-order logic deduction. First we present our framework: simple conceptual graphs, rules as couples of lambda-abstractions, knowledge base, logical… (More)

In ∀∃-rules, the conclusion may contain existen-tially quantified variables, which makes reasoning tasks (as deduction) non-decidable. These rules have the same logical form as TGD (tuple-generating dependencies) in databases and as conceptual graph rules. We extend known decidable cases by combining backward and forward chaining schemes, in association… (More)

This paper focuses on two aspects of piece resolution in backward chaining for conceptual graph rules 13]. First, as conceptual graphs admit a rst-order logic interpretation, inferences can be proven by classical theorem provers. Nevertheless, they do not use the notion of piece, which is a graph notion. So we deene piece resolution over a class of… (More)

- Eric Salvat
- ECAI
- 1998

Conceptual Graphs Rules were proposed as an extension of Simple Conceptual Graphs (CGs) to represent knowledge of form " if A then B " , where A and B are simple CGs. Optimizations of the deduction calculus in this KR formalism include a Backward Chaining that unifies at the same time whole subgraphs of a rule, and a Forward Chaining that relies on… (More)

Simple conceptual graphs can be seen as a very basic description logic, allowing however for answering conjunctive queries. In the first part of this paper, we translate some results obtained for conceptual graph rules of form " if A then B " into an equivalent DL-based formalism. Then we show that, our algorithms can automatically decide in some cases… (More)