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Graph-based Knowledge Representation

Computational Foundations of Conceptual Graphs

Chein, Michel, Mugnier, Marie-Laure

2009, XIV, 428 p.

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  • The first book to provide a comprehensive overview of the computational facets of conceptual graphs
  • Intuitively introduces the main notions of graph theory from a knowledge representation viewpoint, and gives precise definitions of these notions together with complete proofs of the theorems
  • In its provision of strong theoretical bases the book links up fundamental problems in conceptual graphs with important problems in computer science, and contains algorithms for reasoning

This book studies a graph-based knowledge representation and reasoning formalism stemming from conceptual graphs, with a substantial focus on the computational properties.

Knowledge can be symbolically represented in many ways, and the authors have chosen labeled graphs for their modeling and computational qualities.

Key features of the formalism presented can be summarized as follows:

• all kinds of knowledge (ontology, facts, rules, constraints) are labeled graphs, which provide an intuitive and easily understandable means to represent knowledge,

• reasoning mechanisms are based on graph-theoretic operations and this allows, in particular, for linking the basic problem to other fundamental problems in computer science (e.g. constraint networks, conjunctive queries in databases),

• it is logically founded, i.e. it has a logical semantics and the graph inference mechanisms are sound and complete,

• there are efficient reasoning algorithms, thus knowledge-based systems can be built to solve real problems.

In a nutshell, the authors have attempted to answer, the following question:

``how far is it possible to go in knowledge representation and reasoning by representing knowledge with graphs and reasoning with graph operations?''

Content Level » Research

Keywords » Conceptual Graphs - Graph - Graph theory - Hypergraph - Knowledge Representation - Reasoning - Sim - algorithms

Related subjects » Artificial Intelligence - Database Management & Information Retrieval

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