Search (38 results, page 1 of 2)

  • × theme_ss:"Begriffstheorie"
  1. Axelos, C.; Flasch, K.; Schepers, H.; Kuhlen, R.; Romberg, R.; Zimmermann, R.: Allgemeines/Besonderes (1971-2007) 0.06 
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    Footnote
    DOI: 10.24894/HWPh.5033. Vgl. unter: https://www.schwabeonline.ch/schwabe-xaveropp/elibrary/start.xav#__elibrary__%2F%2F*%5B%40attr_id%3D%27verw.allgemeinesbesonderes%27%5D__1515856414979.
  2. Kolmayer, E.; Lavandier, J.; Roger, D.: Conceptual maps : users navigation through paradigmatic and syntagmatic links (1998) 0.02 
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    Abstract
    This experiment, focused on the users behaviour, aims to study the search topic representation they build and to highlight the role of a graphical thesaurus on their mental models and searching behaviour. The users expertise in the field is considered. The results show how difficult it is to structure a field; they also point out how much a graphical thesaurus could contribute to such a task, but also its restricted role in the query task. They urge us to think over which shape is proper to the conceptual interface and the variety of links that have to be taken into account
  3. Mental images in human cognition (1991) 0.01 
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  4. Marradi, A.: ¬The concept of concept : concepts and terms (2012) 0.01 
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    Abstract
    The concept of concept has seldom been examined in its entirety, and the term very seldom defined. The rigidity, or lack thereof, and the homogeneity, or lack thereof, of concepts, are only two of their characteristics that have been debated. These issues are reviewed in this paper, namely: 1) does a concept represent its referent(s), or is it a free creation of the mind?; 2) can a concept be analyzed in parts or elements?; 3) must a concept be general, i.e., refer to a category or a type, or can it refer to a single object, physical or mental?; 4) are concepts as clearly delimited as terms are? Are concepts voiceless terms?; and, 5) what do terms contribute to an individual's and a community's conceptual richness? As regards the relationship of concepts with their referents in the stage of formation, it seems reasonable to conclude that said relationship may be close in some concepts, less close in others, and lacking altogether in some cases. The set of elements of a concept, which varies from individual to individual and across time inside the same individual, is called the intension of a concept. The set of referents of a concept is called the extension of that concept. Most concepts don't have a clearly delimited extension: their referents form a fuzzy set. The aspects of a concept's intension form a scale of generality. A concept is not equal to the term that describes it; rather, many terms are joined to concepts. Language, therefore, renders a gamut of services to the development, consolidation, and communication of conceptual richness.
    Date
    22. 1.2012 13:11:25
    Source
    Knowledge organization. 39(2012) no.1, S.29-54
  5. Klix, F.: ¬Die Natur des Verstandes (1992) 0.01 
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    Date
    3. 3.2008 16:36:29
    LCSH
    Mental Processes
    Subject
    Mental Processes
  6. Jouis, C.: Logic of relationships (2002) 0.01 
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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
  7. Principles of semantic networks : explorations in the representation of knowledge (1991) 0.01 
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    Abstract
    Enthält 3 thematische Sektionen: (1) Issues in knowledge representation; (2) formal analyses; (3) systems for knowledge representation
  8. Jorna, R.J.: Knowledge representation and symbols in the mind : an analysis in cognitive psychology (1990) 0.01 
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  9. Sowa, J.F.: Knowledge representation : logical, philosophical, and computational foundations (2000) 0.01 
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  10. Guarino, N.: Formal ontology, conceptual analysis and knowledge representation (1995) 0.01 
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    Abstract
    Defends the systematic introduction of formal ontological principles in the current practice of knowledge engineering, and explores the various relationships between ontology and knowledge representatiom. Presents recent trends in this research area. Compares the dichotomy between reasoning and representation to the philosophical distinction between epistemology and ontology. Introduces the notion of the ontological level, intermediate between the epistemological and conceptual levels as a way to characterize a knowledge representation formalism taking into account the intended meaning of its primitives
  11. Eckes, T.: Knowledge structures and knowledge representation : psychological models of conceptual order (1990) 0.01 
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  12. Friedman, A.; Thellefsen, M.: Concept theory and semiotics in knowledge organization (2011) 0.01 
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    Abstract
    Purpose - The purpose of this paper is to explore the basics of semiotic analysis and concept theory that represent two dominant approaches to knowledge representation, and explore how these approaches are fruitful for knowledge organization. Design/methodology/approach - In particular the semiotic theory formulated by the American philosopher C.S. Peirce and the concept theory formulated by Ingetraut Dahlberg are investigated. The paper compares the differences and similarities between these two theories of knowledge representation. Findings - The semiotic model is a general and unrestricted model of signs and Dahlberg's model is thought from the perspective and demand of better knowledge organization system (KOS) development. It is found that Dahlberg's concept model provides a detailed method for analyzing and representing concepts in a KOS, where semiotics provides the philosophical context for representation. Originality/value - This paper is the first to combine theories of knowledge representation, semiotic and concept theory, within the context of knowledge organization.
  13. ¬The role of formal ontology in the information technology (1995) 0.00 
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    Abstract
    A special issue devoted to the role of formal ontology in information technology. Papers were given at the International Workshop on Formal Ontology in Conceptual Analysis and Knowledge Representation, held in Padova, Iatly, Mar 95
  14. ¬The semantics of relationships : an interdisciplinary perspective (2002) 0.00 
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    Abstract
    Work on relationships takes place in many communities, including, among others, data modeling, knowledge representation, natural language processing, linguistics, and information retrieval. Unfortunately, continued disciplinary splintering and specialization keeps any one person from being familiar with the full expanse of that work. By including contributions form experts in a variety of disciplines and backgrounds, this volume demonstrates both the parallels that inform work on relationships across a number of fields and the singular emphases that have yet to be fully embraced, The volume is organized into 3 parts: (1) Types of relationships (2) Relationships in knowledge representation and reasoning (3) Applications of relationships
    Content
    Enthält die Beiträge: Pt.1: Types of relationships: CRUDE, D.A.: Hyponymy and its varieties; FELLBAUM, C.: On the semantics of troponymy; PRIBBENOW, S.: Meronymic relationships: from classical mereology to complex part-whole relations; KHOO, C. u.a.: The many facets of cause-effect relation - Pt.2: Relationships in knowledge representation and reasoning: GREEN, R.: Internally-structured conceptual models in cognitive semantics; HOVY, E.: Comparing sets of semantic relations in ontologies; GUARINO, N., C. WELTY: Identity and subsumption; JOUIS; C.: Logic of relationships - Pt.3: Applications of relationships: EVENS, M.: Thesaural relations in information retrieval; KHOO, C., S.H. MYAENG: Identifying semantic relations in text for information retrieval and information extraction; McCRAY, A.T., O. BODENREICHER: A conceptual framework for the biiomedical domain; HETZLER, B.: Visual analysis and exploration of relationships
    Footnote
    Mit ausführlicher Einleitung der Herausgeber zu den Themen: Types of relationships - Relationships in knowledge representation and reasoning - Applications of relationships
  15. Rahmstorf, G.: ¬An integrated conceptual representation for words and phrases (1992) 0.00 
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  16. Conceptual structures : theory, tools and applications. 6th International Conference on Conceptual Structures, ICCS'98, Montpellier, France, August, 10-12, 1998, Proceedings (1998) 0.00 
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    Abstract
    This book constitutes the refereed proceedings of the 6th International Conference on Conceptual Structures, ICCS'98, held in Montpellier, France, in August 1998. The 20 revised full papers and 10 research reports presented were carefully selected from a total of 66 submissions; also included are three invited contributions. The volume is divided in topical sections on knowledge representation and knowledge engineering, tools, conceptual graphs and other models, relationships with logics, algorithms and complexity, natural language processing, and applications.
  17. Thellefsen, M.: ¬The dynamics of information representation and knowledge mediation (2006) 0.00 
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  18. Working with conceptual structures : contributions to ICCS 2000. 8th International Conference on Conceptual Structures: Logical, Linguistic, and Computational Issues. Darmstadt, August 14-18, 2000 (2000) 0.00 
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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)
  19. Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000) 0.00 
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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)
  20. Gerbé, O.; Mineau, G.W.; Keller, R.K.: Conceptual graphs, metamodelling, and notation of concepts : fundamental issues (2000) 0.00 
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    Abstract
    Knowledge management, in particular corporate knowledge management, is a challenge companies and researchers have to meet. The conceptual graph formalism is a good candidate for the representation of corporate knowledge, and for the development of knowledge management systems. But many of the issues concerning the use of conceptual graphs as a metalanguage have not been worked out in detail. By introducing a function that maps higher level to lower level, this paper clarifies the metalevel semantics, notation and manipulation of concepts in the conceptual graph formalism. In addition, this function allows metamodeling activities to take place using the CG notation

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