Conceptual graphs for knowledge representation : First International Conference on Conceptual Structures, ICCS '93, Quebec City, Canada, August 4-7, 1993 : proceedings
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Conceptual graphs for knowledge representation : First International Conference on Conceptual Structures, ICCS '93, Quebec City, Canada, August 4-7, 1993 : proceedings
(Lecture notes in computer science, 699 . Lecture notes in artificial intelligence)
Springer-Verlag, c1993
- : gw
- : us
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
Artificial Intelligence and cognitive science are the two
fields devoted to the study and development of
knowledge-based systems (KBS). Over the past 25years,
researchers have proposed several approaches for modeling
knowledge in KBS, including several kinds of formalism such
as semantic networks, frames, and logics. In the early
1980s, J.F. Sowa introduced the conceptual graph (CG) theory
which provides a knowledge representation framework
consisting of a form of logic with a graph notationand
integrating several features from semantic net and frame
representations. Since that time, several research teams
over the world have been working on the application and
extension of CG theory in various domains ranging from
natural language processing to database modeling and machine
learning.
This volume contains selected papers fromthe international
conference on Conceptual Structures held in the city of
Quebec, Canada, August 4-7, 1993. The volume opens with
invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.
Table of Contents
Relating diagrams to logic.- Representation, discourse, logic and truth: Situating knowledge technology.- Heterogeneous reasoning.- A comparison between conceptual graphs and KL-ONE.- The term definition operators of ontolingua and of the conceptual graph formalism: a comparison.- Implementing conceptual graphs in a RDBMS.- A conceptual graphs approach to conceptual schema integration.- Conceptual graphs for relational Databases.- Inducing a CG representation for basic-level categorization of verbs.- The representation of linguistic information in an approach used for modelling temporal knowledge in discourses.- Representing natural language causality in Conceptual Graphs: The Higher order conceptual relation problem.- Executable conceptual structures.- Inverting resolution with conceptual graphs.- Towards domain-independent machine intelligence.- Efficient retrieval from hierarchies of objects using lattice operations.- Characterization and algorithmic recognition of canonical conceptual graphs.- A conceptual semantics ontology for conceptual graphs.- Acquiring temporal knowledge from schedules.- Conceptual structures for modeling in CIM.- Elicitation of taxonomies based on the use of conceptual graph operators.- Presenting a peirce logic based inference engine and theorem prover for conceptual graphs.- Operations on conceptual structures and Peirce's system of existential graphs.- Modal logics for conceptual graphs.- Fuzzy conceptual graphs.
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