Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
The Unified Modeling Language user guide
The Unified Modeling Language user guide
Knowledge Representation and Reasonings Based on Graph Homomorphism
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
A Datatype Extension for Simple Conceptual Graphs and Conceptual Graphs Rules
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Extensions of simple conceptual graphs: the complexity of rules and constraints
Journal of Artificial Intelligence Research
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Datatypes , like numbers or strings, are widely used in Knowledge Representation (e.g. in RDF(S)/OWL or UML languages). The usual model of simple conceptual graphs does not support datatypes. Some extensions of conceptual graphs have been proposed for using datatypes, however these extensions often wander from initial model of conceptual graphs by introducing for instance procedural relations between nodes. This paper proposes a datatype extension for the simple conceptual graph model. Our contribution is threefold. First, we allow the use of datatypes for typing concept nodes. Second, we define two families of conceptual graphs: factual graphs and query graphs , both close to initial model. Factual graph is used to represent factual knowledge, including values of datatypes. Query graph may contain concept nodes that represent conditional queries on values of datatypes; these conditions are expressed by regular operators on datatypes. Third, we adapt projection to operate from a query graph to a factual graph.