Search (10 results, page 1 of 1)

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Abstract

A main goal of recent studies in semantics is to integrate into conceptual structures the models of representation used in linguistics, logic, and/or artificial intelligence. A fundamental problem resides in the need to structure knowledge and then to check the validity of constructed representations. We propose associating logical properties with relationships by introducing the relationships into a typed and functional system of specifcations. This makes it possible to compare conceptual representations against the relationships established between the concepts. The mandatory condition to validate such a conceptual representation is consistency. The semantic system proposed is based an a structured set of semantic primitives-types, relations, and properties-based an a global model of language processing, Applicative and Cognitive Grammar (ACG) (Desc16s, 1990), and an extension of this model to terminology (Jouis & Mustafa 1995, 1996, 1997). The ACG postulates three levels of representation of languages, including a cognitive level. At this level, the meanings of lexical predicates are represented by semantic cognitive schemes. From this perspective, we propose a set of semantic concepts, which defines an organized system of meanings. Relations are part of a specification network based an a general terminological scheure (i.e., a coherent system of meanings of relations). In such a system, a specific relation may be characterized as to its: (1) functional type (the semantic type of arguments of the relation); (2) algebraic properties (reflexivity, symmetry, transitivity, etc.); and (3) combinatorial relations with other entities in the same context (for instance, the part of the text where a concept is defined).

Date

1.12.2002 11:12:22

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Abstract

The basic conceptual units of cognitive semantics-image schemata, basic level concepts, and frames-are intemally structured, with meaningful relationships existing between components of those units. In metonymy, metaphor, and blended spaces, such intemal conceptual structure is complemented by extemal referential structure, based an mappings between elements of underlying conceptualspaces.

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Abstract

This paper present an alternative approach to knowledge organization based on semiotic reasoning. The semantic distance between domain specific terminology and KOS is analyzed by means of their different sign systems. It is argued that a faceted approach may provide the means needed to minimize the gap between knowledge domains and KOS.

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Abstract

Computer scientists create models of a perceived reality. Through AI techniques, these models aim at providing the basic support for emulating cognitive behavior such as reasoning and learning, which is one of the main goals of the Al research effort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using different paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (first-order logic, modal logic, rule-based systems), virtual reality models (object systems, agent systems), probabilistic models (Bayesian nets, fuzzy logic), linguistic models (conceptual dependency graphs, language-based rep resentations), etc. One of the strengths of the Conceptual Graph (CG) theory is its versatility in terms of the representation paradigms under which it falls. It can be viewed and therefore used, under different representation paradigms, which makes it a popular choice for a wealth of applications. Its full coupling with different cognitive processes lead to the opening of the field toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge. ICCS 2000 embodies this spirit of research collaboration. It presents a set of papers that we believe, by their exposure, will benefit the whole community. For instance, the technical program proposes tracks on Conceptual Ontologies, Language, Formal Concept Analysis, Computational Aspects of Conceptual Structures, and Formal Semantics, with some papers on pragmatism and human related aspects of computing. Never before was the program of ICCS formed by so heterogeneously rooted theories of knowledge representation and use. We hope that this swirl of ideas will benefit you as much as it already has benefited us while putting together this program

Content

Concepts and Language: The Role of Conceptual Structure in Human Evolution (Keith Devlin) - Concepts in Linguistics - Concepts in Natural Language (Gisela Harras) - Patterns, Schemata, and Types: Author Support through Formalized Experience (Felix H. Gatzemeier) - Conventions and Notations for Knowledge Representation and Retrieval (Philippe Martin) - Conceptual Ontology: Ontology, Metadata, and Semiotics (John F. Sowa) - Pragmatically Yours (Mary Keeler) - Conceptual Modeling for Distributed Ontology Environments (Deborah L. McGuinness) - Discovery of Class Relations in Exception Structured Knowledge Bases (Hendra Suryanto, Paul Compton) - Conceptual Graphs: Perspectives: CGs Applications: Where Are We 7 Years after the First ICCS ? (Michel Chein, David Genest) - The Engineering of a CC-Based System: Fundamental Issues (Guy W. Mineau) - Conceptual Graphs, Metamodeling, and Notation of Concepts (Olivier Gerbé, Guy W. Mineau, Rudolf K. Keller) - Knowledge Representation and Reasonings: Based on Graph Homomorphism (Marie-Laure Mugnier) - User Modeling Using Conceptual Graphs for Intelligent Agents (James F. Baldwin, Trevor P. Martin, Aimilia Tzanavari) - Towards a Unified Querying System of Both Structured and Semi-structured Imprecise Data Using Fuzzy View (Patrice Buche, Ollivier Haemmerlé) - Formal Semantics of Conceptual Structures: The Extensional Semantics of the Conceptual Graph Formalism (Guy W. Mineau) - Semantics of Attribute Relations in Conceptual Graphs (Pavel Kocura) - Nested Concept Graphs and Triadic Power Context Families (Susanne Prediger) - Negations in Simple Concept Graphs (Frithjof Dau) - Extending the CG Model by Simulations (Jean-François Baget) - Contextual Logic and Formal Concept Analysis: Building and Structuring Description Logic Knowledge Bases: Using Least Common Subsumers and Concept Analysis (Franz Baader, Ralf Molitor) - On the Contextual Logic of Ordinal Data (Silke Pollandt, Rudolf Wille) - Boolean Concept Logic (Rudolf Wille) - Lattices of Triadic Concept Graphs (Bernd Groh, Rudolf Wille) - Formalizing Hypotheses with Concepts (Bernhard Ganter, Sergei 0. Kuznetsov) - Generalized Formal Concept Analysis (Laurent Chaudron, Nicolas Maille) - A Logical Generalization of Formal Concept Analysis (Sébastien Ferré, Olivier Ridoux) - On the Treatment of Incomplete Knowledge in Formal Concept Analysis (Peter Burmeister, Richard Holzer) - Conceptual Structures in Practice: Logic-Based Networks: Concept Graphs and Conceptual Structures (Peter W. Eklund) - Conceptual Knowledge Discovery and Data Analysis (Joachim Hereth, Gerd Stumme, Rudolf Wille, Uta Wille) - CEM - A Conceptual Email Manager (Richard Cole, Gerd Stumme) - A Contextual-Logic Extension of TOSCANA (Peter Eklund, Bernd Groh, Gerd Stumme, Rudolf Wille) - A Conceptual Graph Model for W3C Resource Description Framework (Olivier Corby, Rose Dieng, Cédric Hébert) - Computational Aspects of Conceptual Structures: Computing with Conceptual Structures (Bernhard Ganter) - Symmetry and the Computation of Conceptual Structures (Robert Levinson) An Introduction to SNePS 3 (Stuart C. Shapiro) - Composition Norm Dynamics Calculation with Conceptual Graphs (Aldo de Moor) - From PROLOG++ to PROLOG+CG: A CG Object-Oriented Logic Programming Language (Adil Kabbaj, Martin Janta-Polczynski) - A Cost-Bounded Algorithm to Control Events Generalization (Gaël de Chalendar, Brigitte Grau, Olivier Ferret)

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Abstract

The intuitive simplicity of the so-called is-a (or subsumption) relationship has led to widespread ontological misuse. Where previous work has focused largely an the semantics of the relationship itself, we concentrate here an the ontological nature of its arguments, in Order to tell whether a single is-a link is ontologically well-founded. For this purpose, we introduce some techniques based an the philosophical notions of identity, unity, and essence, which have been adapted to the needs of taxonomy design. We demonstrate the effectiveness of these techniques by taking real examples of poorly structured taxonomies and revealing cases of invalid generalization.

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Abstract

Specialized domains often come with an extensive terminology, suitable for storing and exchanging information, but not necessarily for knowledge processing. Knowledge structures such as semantic networks, or ontologies, are required to explore the semantics of a domain. The UMLS project at the National Library of Medicine is a research effort to develop knowledge-based resources for the biomedical domain. The Metathesaurus is a large body of knowledge that defines and inter-relates 730,000 biomedical concepts, and the Semantic Network defines the semantic principles that apply to this domain. This chapter presents these two knowledge sources and illustrates through a research study how they can collaborate to further structure the domain. The limits of the approach are discussed.

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Abstract

Concept theory is an extremely broad, interdisciplinary and complex field of research related to many deep fields with very long historical traditions without much consensus. However, information science and knowledge organization cannot avoid relating to theories of concepts. Knowledge organizing systems (e.g., classification systems, thesauri, and ontologies) should be understood as systems basically organizing concepts and their semantic relations. The same is the case with information retrieval systems. Different theories of concepts have different implications for how to construe, evaluate, and use such systems. Based on a post-Kuhnian view of paradigms, this article put forward arguments that the best understanding and classification of theories of concepts is to view and classify them in accordance with epistemological theories (empiricism, rationalism, historicism, and pragmatism). It is also argued that the historicist and pragmatist understandings of concepts are the most fruitful views and that this understanding may be part of a broader paradigm shift that is also beginning to take place in information science. The importance of historicist and pragmatic theories of concepts for information science is outlined.

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Content

Concepts & Language: Knowledge organization by procedures of natural language processing. A case study using the method GABEK (J. Zelger, J. Gadner) - Computer aided narrative analysis using conceptual graphs (H. Schärfe, P. 0hrstrom) - Pragmatic representation of argumentative text: a challenge for the conceptual graph approach (H. Irandoust, B. Moulin) - Conceptual graphs as a knowledge representation core in a complex language learning environment (G. Angelova, A. Nenkova, S. Boycheva, T. Nikolov) - Conceptual Modeling and Ontologies: Relationships and actions in conceptual categories (Ch. Landauer, K.L. Bellman) - Concept approximations for formal concept analysis (J. Saquer, J.S. Deogun) - Faceted information representation (U. Priß) - Simple concept graphs with universal quantifiers (J. Tappe) - A framework for comparing methods for using or reusing multiple ontologies in an application (J. van ZyI, D. Corbett) - Designing task/method knowledge-based systems with conceptual graphs (M. Leclère, F.Trichet, Ch. Choquet) - A logical ontology (J. Farkas, J. Sarbo) - Algorithms and Tools: Fast concept analysis (Ch. Lindig) - A framework for conceptual graph unification (D. Corbett) - Visual CP representation of knowledge (H.D. Pfeiffer, R.T. Hartley) - Maximal isojoin for representing software textual specifications and detecting semantic anomalies (Th. Charnois) - Troika: using grids, lattices and graphs in knowledge acquisition (H.S. Delugach, B.E. Lampkin) - Open world theorem prover for conceptual graphs (J.E. Heaton, P. Kocura) - NetCare: a practical conceptual graphs software tool (S. Polovina, D. Strang) - CGWorld - a web based workbench for conceptual graphs management and applications (P. Dobrev, K. Toutanova) - Position papers: The edition project: Peirce's existential graphs (R. Mülller) - Mining association rules using formal concept analysis (N. Pasquier) - Contextual logic summary (R Wille) - Information channels and conceptual scaling (K.E. Wolff) - Spatial concepts - a rule exploration (S. Rudolph) - The TEXT-TO-ONTO learning environment (A. Mädche, St. Staab) - Controlling the semantics of metadata on audio-visual documents using ontologies (Th. Dechilly, B. Bachimont) - Building the ontological foundations of a terminology from natural language to conceptual graphs with Ribosome, a knowledge extraction system (Ch. Jacquelinet, A. Burgun) - CharGer: some lessons learned and new directions (H.S. Delugach) - Knowledge management using conceptual graphs (W.K. Pun)

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Pages

S.22-33

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Date

11.12.2019 19:00:22