Conceptual Graphs for Knowledge Representation : First International Conference on Conceptual Structures, ICCS'93, Quebec City, Canada, August 4-7, 19

Mineau, Guy W.

ISBN 10: 3540569790 / ISBN 13: 9783540569794

Editore: Springer 1993-07, 1993

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Codice articolo 6666-IUK-9783540569794

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Titolo: Conceptual Graphs for Knowledge ...

Casa editrice: Springer 1993-07

Data di pubblicazione: 1993

Legatura: PF

Condizione: New

Descrizione articolo

Riassunto:

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.

Contenuti:

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.