- (Corbett, 2008) ⇒ Dan R. Corbett. (2008). “[Graph-based Representation and Reasoning for Ontologies].” In: Studies in Computational Intelligence, Springer. [http://dx.doi.org/10.1007/978-3-540-78293-3 10.1007/978-3-540-78293-3 doi:[http://dx.doi.org/10.1007/978-3-540-78293-3 10.1007/978-3-540-78293-3)
- It contains a definition for:
- Canon, Concept Type, Relation Type, Type Set, Individual, Subtype Relation, Conformity Relation, Canonical Basis Function,
- Conceptual Graph, Concept Type, Conceptual Relation, Relation Type, Function-Arity Function,
- Canonical Graph, Subsumption Relation, Ontology.
- Domain, Concept Type, Relation Type, Individual.
- Concept Type Projection, Referent, Referent Marker, Description Logics, Concept Type Hierarchy,
- ~0 http://scholar.google.com/scholar?q=%22Graph-Based+Representation+and+Reasoning+for+Ontologies%22+2008
An ontology, in the Knowledge Engineering and Artificial Intelligence sense, is a framework for the domain knowledge of an intelligent system. An ontology structures the knowledge, and acts as a container for the knowledge. We define knowledge conjunction as one or more agents using multiple ontologies to perform tasks and understand the domain. Once a common ontology is agreed upon, the agents then have a common background in which to share knowledge. No current method exists that allows intelligent agents to agree on a common framework for sharing knowledge, although there has been some work in comparing semantic meanings within an ontology . This means that agents are unable to use the knowledge of another agent, as the knowledge is meaningless if it isn’t presented in a proper context or a common ‘language’.
In this Chapter, we first give an overview of Conceptual Graph Theory, including what conceptual graphs are and how they work. We then take a different point-of-view for the representation of ontologies. Rather than constructing a CG to represent the ontology, we assert that the CG formalism is better exploited by using a combination of the concept type hierarchy, the canonical formation rules, the conformity relation and subsumption to act as the framework for the knowledge base. An unpopulated ontology (which is simply a framework for the knowledge) is represented by the type hierarchy without specific individuals, while the populated ontology (the framework, as well as the knowledge of the domain) is represented by a hierarchy and the specific conceptual graphs which instantiate individuals, constraints, situations or concepts.,
|2008 GraphBasedRemAndReasforOntologies||Dan R. Corbett||Graph-based Representation and Reasoning for Ontologies||Studies in Computational Intelligence||http://dx.doi.org/10.1007/978-3-540-78293-3||10.1007/978-3-540-78293-3||2008|