-
Axelos, C.; Flasch, K.; Schepers, H.; Kuhlen, R.; Romberg, R.; Zimmermann, R.: Allgemeines/Besonderes (1971-2007)
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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.
-
Pathak, L.P.: Concept-term relationship and a classified schedule of isolates for the term 'concept' (2000)
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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
-
Bonnevie, E.: Dretske's semantic information theory and meta-theories in library and information science (2001)
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- Abstract
- This article presents the semantic information theory, formulated by the philosopher Fred I. Dretske, as a contribution to the discussion of metatheories and their practical implications in the field of library and information science. Dretske's theory is described in Knowledge and the flow of information. It is founded on mathematical communication theory but developed and elaborated into a cognitive, functionalistic theory, is individually oriented, and deals with the content of information. The topics are: the information process from perception to cognition, and how concept formation takes place in terms of digitisation. Other important issues are the concepts of information and knowledge, truth and meaning. Semantic information theory can be used as a frame of reference in order to explain, clarify and refute concepts currently used in library and information science, and as the basis for critical reviews of elements of the cognitive viewpoint in IR, primarily the notion of "potential information". The main contribution of the theory lies in a clarification of concepts, but there are still problems regarding the practical applications. More research is needed to combine philosophical discussions with the practice of information and library science.
-
Thiel, C.: ¬Der klassische und der moderne Begriff des Begriffs : Gedanken zur Geschichte der Begriffsbildung in den exakten Wissenschaften (1994)
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- Abstract
- Up to the present day, difficulties have confronted all attempts at establishing a theory of concepts that would comprise the various kinds of concept-formation in the disciplines of the spectrum of sciences. Not a few philosophical dictionaries, under the entry 'concept', still offer doctrinies which were current far back in the history of philosophy and have little in coomon with concept-formations in the sciences today. The paper aims at an improvement in this situation. After a sketch of the 'classical' notion of concept, already developed in antiquity (essentially a logic of 'classification', although 'class-formation' in tis present understanding had not yet been conceived), the canonical modern doctrine of concepts is outlined. With an eye to application in the exact sciences, it is shown how in the nineteenth century the view of concept as an additive complex of characteristics yields to a functional approach systematized, in the last quarter of the century, by classical quantificational logic. Almost simultaneously, Mach, Frege, Peano, Weyl and others set out to shape the modern theory of abstraction. It is these two theories that today permit philosophers of science not only to deal with functional processes of concept-formation but also to represent in a formally coorect manner metalinguistic propositions about concepts and their properties. Thus it seems that the fundamental tasks of a modern theory of concept have finally been taken care of
- 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
-
Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000)
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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)
- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Hjoerland, B.: Concept theory (2009)
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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.
- Footnote
- Vgl.: Szostak, R.: Comment on Hjørland's concept theory in: Journal of the American Society for Information Science and Technology. 61(2010) no.5, S. 1076-1077 und die Erwiderung darauf von B. Hjoerland (S.1078-1080)
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1519-1536
-
Khoo, C.; Myaeng, S.H.: Identifying semantic relations in text for information retrieval and information extraction (2002)
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- Abstract
- Automatic identification of semantic relations in text is a difficult problem, but is important for many applications. It has been used for relation matching in information retrieval to retrieve documents that contain not only the concepts but also the relations between concepts specified in the user's query. It is an integral part of information extraction-extracting from natural language text, facts or pieces of information related to a particular event or topic. Other potential applications are in the construction of relational thesauri (semantic networks of related concepts) and other kinds of knowledge bases, and in natural language processing applications such as machine translation and computer comprehension of text. This chapter examines the main methods used for identifying semantic relations automatically and their application in information retrieval and information extraction.
- Series
- Information science and knowledge management; vol.3
-
¬The semantics of relationships : an interdisciplinary perspective (2002)
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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
- Series
- Information science and knowledge management; vol.3
-
Hjoerland, B.: Are relations in thesauri "context-free, definitional, and true in all possible worlds"? (2015)
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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.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.7, S.1367-1373
-
Pansegrouw, J.G.: ¬Die begrippe spesie, klas en versameling in verhouding tot indekseringteorie (1995)
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- Source
- South African journal of library and information science. 63(1995) no.4, S.173-178
-
Treude, L.: ¬Das Problem der Konzeptdefinition in der Wissensorganisation : über einen missglückten Versuch der Klärung (2013)
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- Source
- LIBREAS: Library ideas. no.22, 2013, S.xx-xx
-
Garcia Marco, F.J.; Esteban Navarro, M.A.: On some contributions of the cognitive sciences and epistemology to a theory of classification (1993)
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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'
-
Gerbé, O.; Mineau, G.W.; Keller, R.K.: Conceptual graphs, metamodelling, and notation of concepts : fundamental issues (2000)
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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
- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Machado, L.M.O.; Martínez-Ávila, D.; Simões, M.da Graça de Melo: Concept theory in library and information science : an epistemological analysis (2019)
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- Abstract
- Purpose The purpose of this paper is to discuss the literature on concept theory in library and information science (LIS) from an epistemological perspective, ascribing each paper to an epistemological family and discussing their relevance in the context of the knowledge organization (KO) domain. Design/methodology/approach This paper adopts a hermeneutic approach for the analysis of the texts that compose the corpus of study following contingency and categorical analyses. More specifically, the paper works with Bardin's contingency analysis and follows Hjørland's families of epistemologies for the categorization. Findings The analysis corroborates the observations made for the last ten years about the scarcity of studies on concept theory in LIS and KO. However, the study also reveals an epistemological turn on concept theory since 2009 that could be considered a departure from the rationalist views that dominated the field and a continuation of a broader paradigm shift in LIS and KO. All analyzed papers except two follow pragmatist or historicist approaches. Originality/value This paper follows-up and systematizes the contributions to the LIS and KO fields on concept theory mainly during the last decade. The epistemological analysis reveals the dominant views in this paradigm shift and the main authors and trends that are present in the LIS literature on concept theory.
-
Sekhar, M.; Ekbote, E.R.: Cognitive skills of conceptualisation process and types of concepts (1992)
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- Imprint
- Bangalore : Sarada Ranganathan Endowment for Library Science
-
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)
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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)
-
Olson, H.A.: How we construct subjects : a feminist analysis (2007)
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- Date
- 11.12.2019 19:00:22
- Source
- Library trends. 56(2007) no.2, S.509-541
-
McCray, A.T.; Bodenreider, O.: ¬A conceptual framework for the biomedical domain (2002)
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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.
- Series
- Information science and knowledge management; vol.3
-
Marradi, A.: ¬The concept of concept : concepts and terms (2012)
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- Date
- 22. 1.2012 13:11:25
- Source
- Knowledge organization. 39(2012) no.1, S.29-54
-
Nelson, S.J.: From meaning to term : semantic locality in the UMLS metathesaurus (1992)
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- Source
- Assessing the value of medical informatics: Proc. of the 15th Annual Symposium on Computer Applications in Medical Care, Washington, DC, Nov.1991
