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  • × language_ss:"e"
  • × theme_ss:"Begriffstheorie"
  1. Dahlberg, I.: On the theory of the concept (1979) 0.02 
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    Source
    Ordering systems for global information networks. Proc. of the 3rd Int. Study Conf. on Classification Research, Bombay 1975
  2. Svenonius, E.: Indexical contents (1982) 0.02 
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    Universal classification I: subject analysis and ordering systems. Proc. of the 4th Int. Study Conf. on Classification research, Augsburg, 28.6.-2.7.1982. Ed.: I. Dahlberg
  3. Sowa, J.F.: Top-level ontological categories (1995) 0.02 
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    Abstract
    Surveys ontological questions that arise in artificial intelligence, some of the answers that have been proposed by various philosophers, and an application of the philosophical analysis to the clarification of some current issues in artificial intelligence. Charles Sanders Peirce and Alfred North Whitehead have developed the most complete systems of categories. Their analyses suggest a basic structure of categories that can provide some guidelines for the design of artificial intelligence systems
  4. Hjoerland, B.: Concept theory (2009) 0.02 
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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.
  5. 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
  6. Storms, G.; VanMechelen, I.; DeBoeck, P.: Structural-analysis of the intension and extension of semantic concepts (1994) 0.01 
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    Date
    22. 7.2000 19:17:40
  7. Hjoerland, B.: Concepts, paradigms and knowledge organization (2010) 0.01 
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    Abstract
    It is argued that concepts are the building blocks of knowledge organizing systems (KOS). Objections to this view are considered and answers are provided. By implication the theory of concepts constitutes the foundation for knowledge organization (KO). The theory of concepts is understood as related to and derived from theories of knowledge. Different theories of knowledge such as empiricism, rationalism, historicism and pragmatism imply different theories of concepts. Such different epistemologies and their associated theories of concepts represent different methodological ideals which probably compete in all knowledge domains. Different approaches to KO are also in fundamental ways associated with different theories of concepts. The paper holds that the historicist and pragmatic theory of concept should be considered most valuable. By implication is it is necessary to know about competing theories in the fields being organized. A further implication of the pragmatic view is that the construction of a KOS must be understood as a way of participating in the discourses in the domain that is being represented.
    Source
    Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome, Italy. Edited by Claudio Gnoli and Fulvio Mazzocchi
  8. Simoes, G.; Machado, L.; Gnoli, C.; Souza, R.: Can an ontologically-oriented KO do without concepts? (2020) 0.01 
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    Abstract
    The ontological approach in the development of KOS is an attempt to overcome the limitations of the traditional epistemological approach. Questions raise about the representation and organization of ontologically-oriented KO units, such as BFO universals or ILC phenomena. The study aims to compare the ontological approaches of BFO and ILC using a hermeneutic approach. We found that the differences between the units of the two systems are primarily due to the formal level of abstraction of BFO and the different organizations, namely the grouping of phenomena into ILC classes that represent complex compounds of entities in the BFO approach. In both systems the use of concepts is considered instrumental, although in the ILC they constitute the intersubjective component of the phenomena whereas in BFO they serve to access the entities of reality but are not part of them.
  9. Thellefsen, M.: ¬The dynamics of information representation and knowledge mediation (2006) 0.01 
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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.
  10. Hjoerland, B.: Are relations in thesauri "context-free, definitional, and true in all possible worlds"? (2015) 0.01 
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    Abstract
    Much of the literature of information science and knowledge organization has accepted and built upon Elaine Svenonius's (2004) claim that "paradigmatic relationships are those that are context-free, definitional, and true in all possible worlds" (p. 583). At the same time, the literature demonstrates a common understanding that paradigmatic relations are the kinds of semantic relations used in thesauri and other knowledge organization systems (including equivalence relations, hierarchical relations, and associative relations). This understanding is problematic and harmful because it directs attention away from the empirical and contextual basis for knowledge-organizing systems. Whether A is a kind of X is certainly not context-free and definitional in empirical sciences or in much everyday information. Semantic relations are theory-dependent and, in biology, for example, a scientific revolution has taken place in which many relations have changed following the new taxonomic paradigm named "cladism." This biological example is not an exception, but the norm. Semantic relations including paradigmatic relations are not a priori but are dependent on subject knowledge, scientific findings, and paradigms. As long as information scientists and knowledge organizers isolate themselves from subject knowledge, knowledge organization cannot possibly progress.
  11. Pathak, L.P.: Concept-term relationship and a classified schedule of isolates for the term 'concept' (2000) 0.01 
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    Abstract
    Draws attention to the efforts to define the terms 'concept' and 'term' and suggests a schedule of isolates for the term 'concept' under eight headings: 0. Concept; 1. Theoretical aspects; 2. Learning theory and Psychological aspects; 3. Origin, evolution, formation, construction; 4. Semantic aspects; 5.Terms and Terminology; 6. Usage and discipline-specific applications; and 7. Concepts and ISAR systems. The schedule also includes about 150 aspects/isolate terms related to 'concept' along with the name of the authors who have used them. The schedule is intended to help in identifying the various aspects of a concept with the help of the terms used for them. These aspects may guide to some extent, in dissecting and seeing the social science concepts from various point of views
  12. Jouis, C.: Logic of relationships (2002) 0.01 
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    Date
    1.12.2002 11:12:22
  13. Marradi, A.: ¬The concept of concept : concepts and terms (2012) 0.01 
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    Date
    22. 1.2012 13:11:25
  14. Besler, G.; Szulc, J.: Gottlob Frege's theory of definition as useful tool for knowledge organization : definition of 'context' - case study (2014) 0.01 
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  15. Olson, H.A.: How we construct subjects : a feminist analysis (2007) 0.01 
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    Date
    11.12.2019 19:00:22
  16. Garcia Marco, F.J.; Esteban Navarro, M.A.: On some contributions of the cognitive sciences and epistemology to a theory of classification (1993) 0.01 
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    Abstract
    Intended is first of all a preliminary review of the implications that the new approaches to the theory of classification, mainly from cognitive psychology and epistemology may have for information work and research. As a secondary topic the scientific relations existing among information science, epistemology and the cognitive sciences are discussed. Classification is seen as a central activity in all daily and scientific activities, and, of course, of knowledge organization in information services. There is a mutual implication between classification and conceptualization, as the former moves in a natural way to the latter and the best result elaborated for classification is the concept. Research in concept theory is a need for a theory of classification. In this direction it is of outstanding importance to integrate the achievements of 'natural concept formation theory' (NCFT) as an alternative approach to conceptualization different from the traditional one of logicians and problem solving researchers. In conclusion both approaches are seen as being complementary: the NCFT approach being closer to the user and the logical one being more suitable for experts, including 'expert systems'
  17. Gerbé, O.; Mineau, G.W.; Keller, R.K.: Conceptual graphs, metamodelling, and notation of concepts : fundamental issues (2000) 0.01 
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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
  18. Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000) 0.01 
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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
  19. 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)

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