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Date

11.12.2019 19:00:22

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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'

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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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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

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Source

Information systems and data analysis: prospects - foundations - applications. Proc. of the 17th Annual Conference of the Gesellschaft für Klassifikation, Kaiserslautern, March 3-5, 1993. Ed.: H.-H. Bock et al

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Content

Enthält u.a. die Beiträge: WÜSTER, E.: Terminologielehre; HAJUTIN, A.D.: Die verschiedenen Richtungen in der Terminologiearbeit; KOCOUREK, R.: Der Terminus und seine Definition; DROZD, L.: Zum Gegenstand und zur Methode der Terminologielehre; HORECKY, J.: Zu Bedeutungsbeziehungen zwischen den terminologischen Benennungen; FILIPEC, J.: Zur Spezifik des spezialsprachlichen Wortschatzes gegenüber dem allgemeinen Wortschatz; FILIPEC, J.: Zur Frage des Systems in der Terminologie; REFORMATSKIJ, A.A.: Was ist eine Benennung und was ist Terminologie?; SUPERANSKAJA, A.V.: Theoretische Terminologiearbeit; ZHURAVLEV, V.F. u. G.G. SAMBUROVA: Philosophisch-logische Aspekte der Terminologieregelung und -normung; ZHURAVLEV, V.F.: Einige logisch-methodologische Fragen der Regelung des Begriffsapparates und von Terminologien; NALEPIN, V.L.: Begriffsarten und Definitionsstruktur; WÜSTER, E.: Das Worten der Welt, schaubildlich und terminologisch dargestellt; WÜSTER, E.: Die Allgemeine Terminologielehre: ein Grenzgebiet zwischen Sprachwissenschaft, Logik, Ontologie, Informatik und den Sachwissenschaften; FELBER, H.: Einige Grundfragen der Terminologiewissenschaft aus der Sicht der Allgemeinen Terminologielehre; COLE, W.D.: Terminologie: Grundsätze und Methoden; SCHULZE, E.: Der Terminus: Eigenschaften und Wesen sowie seine Abgrenzung von anderen Lexemarten; PICHT, H.: Fachsprachliche Phraseologie; OESER, E.: Terminologie als Voraussetzung der Wissenstechnik; BUDIN, G., C. GALINSKI, W. NEDOBITY u. R. THALLER: Terminologie und die Wissensverarbeitung; PICHT, H. u. C. LAURÉN: Vergleich der terminologischen Schulen

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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)