Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Incremental constraint satisfaction in logic programming
Logic programming
Projection and Unification for Conceptual Graphs
ICCS '95 Proceedings of the Third International Conference on Conceptual Structures: Applications, Implementation and Theory
Towards Fuzzy Conceptual Graph Programs
ICCS '96 Proceedings of the 4th International Conference on Conceptual Structures: Knowledge Representation as Interlingua
Fuzzy Unification and Resolution Proof Procedure for Fuzzy Conceptual Graph Programs
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
Conceptual Graphs and Formal Concept Analysis
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
The Representation of Semantic Constraints in Conceptual Graph Systems
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
A Semantic Validation of Conceptual Graphs
ICCS '98 Proceedings of the 6th International Conference on Conceptual Structures: Theory, Tools and Applications
A Method for Reasoning with Ontologies Represented as Conceptual Graphs
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Reasoning with Ontologies by Using Knowledge Conjunction in Conceptual Graphs
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Lattice-Structured Domains, Imperfect Data and Inductive Queries
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
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The Conceptual Structures community has recently shown increased interest in methods and formalisms for the use of constraints in Conceptual Graphs (CGs), especially the definition of unification over constraints. None of the recent proposed constraint methods, however, are able to use simple unification methods, and still guarantee that a graph which is structurally valid under the canonical formation rules is also semantically valid in the knowledge domain. Our approach defines a method (and concept type) for constraining real values in the referent of a concept. The significance of our work is that a simple unification operation, using join and type subsumption, is defined which can be used to validate the constraints over an entire unified graph. A useful side-effect is that this constraint method can also be used to define real numbers in a referent.