Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.

Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, including several kinds of formalism suchas semantic networks, frames, and logics. In the early1980s, J.F. Sowa introduced the conceptual graph (CG) theorywhich provides a knowledge representation frameworkconsisting of a form of logic with a graph notationandintegrating several features from semantic net and framerepresentations. Since that time, several research teamsover the world have been working on the application andextension of CG theory in various domains ranging fromnatural language processing to database modeling and machinelearning.This volume contains selected papers fromthe internationalconference on Conceptual Structures held in the city ofQuebec, Canada, August 4-7, 1993. The volume opens withinvited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.

This book is the proceedings of the Second International Conference on Conceptual Structures, ICCS '94, held at College Park, Maryland, USA in August 1994.This proceedings presents, on an international scale, up-to- the-minute research results on theoretical and applicational aspects of conceptual graphs, particularly on the use of contexts in knowledge representation. The concept of contexts is highly important for all kinds of knowledge-intensive systems. The book is organized into sections on natural language understanding, rational problem solving, conceptual graph theory, contexts and canons, and data modeling.

Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.

Artificial Intelligence and cognitive science are the twofields devoted to the study and development ofknowledge-based systems (KBS). Over the past 25years,researchers have proposed several approaches for modelingknowledge in KBS, including several kinds of formalism suchas semantic networks, frames, and logics. In the early1980s, J.F. Sowa introduced the conceptual graph (CG) theorywhich provides a knowledge representation frameworkconsisting of a form of logic with a graph notationandintegrating several features from semantic net and framerepresentations. Since that time, several research teamsover the world have been working on the application andextension of CG theory in various domains ranging fromnatural language processing to database modeling and machinelearning.This volume contains selected papers fromthe internationalconference on Conceptual Structures held in the city ofQuebec, Canada, August 4-7, 1993. The volume opens withinvited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.

This book is the proceedings of the Second International Conference on Conceptual Structures, ICCS '94, held at College Park, Maryland, USA in August 1994.This proceedings presents, on an international scale, up-to- the-minute research results on theoretical and applicational aspects of conceptual graphs, particularly on the use of contexts in knowledge representation. The concept of contexts is highly important for all kinds of knowledge-intensive systems. The book is organized into sections on natural language understanding, rational problem solving, conceptual graph theory, contexts and canons, and data modeling.