A Graph-based Knowledge Representation and Reasoning Model
Key features of GBKR, the graph-based knowledge representation and reasoning model developed by Chein and Mugnier and the Montpellier group (Chein & Mugnier 2009), can be summarized as follows:
- all kinds of knowledge (ontology, rules, constraints and facts) are labeled graphs, which provide an intuitive and easily understandable means to represent knowledge,
- reasoning mechanisms are based on graph notions, basically the classical notion of graph homomorphism; this allows, in particular, to link basic reasoning problems to other fundamental problems in computer science (problems on conjunctive queries in relational databases, constraint satisfaction problem, ...),
- the formalism is logically founded, i.e., it has a semantics in first-order logic and the inference mechanisms are sound and complete with respect to deduction in first-order logic,
- from a computational viewpoint, the graph homomorphism notion was recognized in the 90s as a central notion, and complexity results and efficient algorithms have been obtained in several domains.
COGITANT and COGUI are tools that implement the GBKR model. COGITANT is a library of C++ classes that implement most of the GBKR notions and reasoning mechanisms. COGUI is a graphical user interface dedicated to the construction of a GBKR knowledge base (it integrates COGITANT and, among numerous functionalities, it contains a translator from GBKR to RDF/S and conversely).
Read more about this topic: Conceptual Graph
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