Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs / Edition 1

by Michel Chein, Marie-Laure Mugnier

Overview

This book provides a definition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmic qualities of graphs have long been studied, as in databases and constraint networks.

Product Details

ISBN-13:	9781848002852
Publisher:	Springer London
Publication date:	10/08/2008
Series:	Advanced Information and Knowledge Processing
Edition description:	2009
Pages:	428
Product dimensions:	6.40(w) x 9.30(h) x 1.20(d)

Table of Contents

Foundations: Basic and Simple Conceptual Graphs.- Basic Conceptual Graphs.- Simple Conceptual Graphs.- Formal Semantics of SGs.- BG Homomorphism and Equivalent Notions.- Computational Aspects of Basic Conceptual Graphs.- Basic Algorithms for BG Homomorphism.- Tractable Cases.- Other Specialization/Generalization Operations.- Extensions.- Nested Conceptual Graphs.- Rules.- The BG Family: Facts, Rules and Constraints.- Conceptual Graphs with Negation.- An Application of Nested Typed Graphs: Semantic Annotation Bases.

Editorial Reviews

From the reviews:

"This well-written book is a wonderful text for researchers working on theoretical artificial intelligence (AI). Fundamentally, AI represents knowledge with mathematical objects and then designs computational rules to manipulate these objects. … In summary, this is a theoretical book for a graph-based approach to knowledge representation. … A number of detailed algorithms presented in the book may serve as good references for designing a variety of AI systems, such as database mining and logic reasoning." (Hsun-Hsien Chang, ACM Computing Reviews, April, 2009)

From the Publisher