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  1. Evens, M.: Thesaural relations in information retrieval (2002) 0.01
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    Abstract
    Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments
    Series
    Information science and knowledge management; vol.3
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. 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
    Series
    Information science and knowledge management; vol.3
  3. Khoo, C.; Myaeng, S.H.: Identifying semantic relations in text for information retrieval and information extraction (2002) 0.01
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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
  4. Hetzler, B.: Visual analysis and exploration of relationships (2002) 0.01
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    Abstract
    Relationships can provide a rich and powerful set of information and can be used to accomplish application goals, such as information retrieval and natural language processing. A growing trend in the information science community is the use of information visualization-taking advantage of people's natural visual capabilities to perceive and understand complex information. This chapter explores how visualization and visual exploration can help users gain insight from known relationships and discover evidence of new relationships not previously anticipated.
    Series
    Information science and knowledge management; vol.3
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Casagrande, J.B.; Hale, K.L.: Semantic relations in Papago folk definitions (1967) 0.00
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    Footnote
    Zitiert in: Evens, M.: Thesaural relations in information retrieval. In: The semantics of relationships: an interdisciplinary perspective. Eds: R. Green u.a. Dordrecht: Kluwer 2002. S.143-160.
  6. ¬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
    Series
    Information science and knowledge management; vol.3
  7. Hjoerland, B.: Concept theory (2009) 0.00
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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
    Theme
    Information
  8. Nakamura, Y.: Subdivisions vs. conjunctions : a discussion on concept theory (1998) 0.00
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    Abstract
    After studying the relations between two words(nouns) that constitute a compound term, the relation between corresponding concepts discussed. The impossibility of having a conjunction between two concepts that have no common feature causes inconvenience in the application of concept theory to information retrieval problems. Another kind of conjunctions, different from that by co-occurrence, is proposed and characteristics of this conjunction is studied. It revealed that one of new ones has the same character with colon combination in UDC. The possibility of having three kinds of conjunction including Wsterian concept conjunction is presented. It is also discussed that subdivisions can be replaced by new conjunctions
  9. Hovy, E.: Comparing sets of semantic relations in ontologies (2002) 0.00
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    Series
    Information science and knowledge management; vol.3
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  10. O'Neill, E.T.; Kammerer, K.A.; Bennett, R.: ¬The aboutness of words (2017) 0.00
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    Abstract
    Word aboutness is defined as the relationship between words and subjects associated with them. An aboutness coefficient is developed to estimate the strength of the aboutness relationship. Words that are randomly distributed across subjects are assumed to lack aboutness and the degree to which their usage deviates from a random pattern indicates the strength of the aboutness. To estimate aboutness, title words and their associated subjects are extracted from the titles of non-fiction English language books in the OCLC WorldCat database. The usage patterns of the title words are analyzed and used to compute aboutness coefficients for each of the common title words. Words with low aboutness coefficients (An and In) are commonly found in stop word lists, whereas words with high aboutness coefficients (Carbonate, Autism) are unambiguous and have a strong subject association. The aboutness coefficient potentially can enhance indexing, advance authority control, and improve retrieval.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2471-2483
  11. 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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    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)
  12. Olson, H.A.: How we construct subjects : a feminist analysis (2007) 0.00
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    Abstract
    To organize information, librarians create structures. These structures grow from a logic that goes back at least as far as Aristotle. It is the basis of classification as we practice it, and thesauri and subject headings have developed from it. Feminist critiques of logic suggest that logic is gendered in nature. This article will explore how these critiques play out in contemporary standards for the organization of information. Our widely used classification schemes embody principles such as hierarchical force that conform to traditional/Aristotelian logic. Our subject heading strings follow a linear path of subdivision. Our thesauri break down subjects into discrete concepts. In thesauri and subject heading lists we privilege hierarchical relationships, reflected in the syndetic structure of broader and narrower terms, over all other relationships. Are our classificatory and syndetic structures gendered? Are there other options? Carol Gilligan's In a Different Voice (1982), Women's Ways of Knowing (Belenky, Clinchy, Goldberger, & Tarule, 1986), and more recent related research suggest a different type of structure for women's knowledge grounded in "connected knowing." This article explores current and potential elements of connected knowing in subject access with a focus on the relationships, both paradigmatic and syntagmatic, between concepts.
    Content
    Beitrag in einem Themenheft 'Gender Issues in Information Needs and Services'.
    Date
    11.12.2019 19:00:22
  13. Weissenhofer, P.: Conceptology in terminology : theory, semantics, and word-formation. A morpho-conceptually based approach to classification as exemplified by the English baseball terminology (1995) 0.00
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    Abstract
    This dissertation from the University of Vienna contains the following chapters: (1) Conceptological aspects in terminology theory. Post-Wüsterian sign models and the four-field model. Vagueness, prototypes, and the four-field model. Morphological aspects of terminology and prototype theory. Word-formation and its role in terminology theory and conceptology. (2) A morpho-conceptual classification system of the English baseball terminology. The classification system. Statistical results. Conclusions
  14. 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)
  15. Principles of semantic networks : explorations in the representation of knowledge (1991) 0.00
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Hudon, M.: Preparing terminological definitions for indexing and retrieval thesauri : a model (1996) 0.00
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  17. Dahlberg, I.: Concepts and terms : ISKO's major challenge (2009) 0.00
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    Abstract
    Starting from the premise that extant knowledge of the discipline of Knowledge Organization ought to be made accessible by its knowledge units (concepts) this article includes short descriptions of the work of E.Wuester (Austria) and F. Riggs (USA) who both had laid foundations in this field. A noematic concept of knowledge (Diemer 1962, 474) is used for the necessary work to be done. It is shown how a concept-theoretical approach (relying on the characteristics of concepts and their system-building capacity) can be applied for pertinent terminological work. Earlier work in this regard by standardization bodies is mentioned. Seven necessary steps towards accomplishment are outlined.
  18. Bivins, K.T.: Concept formation : the evidence from experimental psychology and linguistics and its relationship to information science (1980) 0.00
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    Source
    Theory and application of information research. Proc. of the 2nd Int. Research Forum on Information Science, 3.-6.8.1977, Copenhagen. Ed.: O. Harbo u. L. Kajberg
  19. Thellefsen, M.M.; Thellefsen, T.; Sørensen, B.: Information as signs : a semiotic analysis of the information concept, determining its ontological and epistemological foundations (2018) 0.00
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    Abstract
    The purpose of this paper is to formulate an analytical framework for the information concept based on the semiotic theory. Design/methodology/approach The paper is motivated by the apparent controversy that still surrounds the information concept. Information, being a key concept within LIS, suffers from being anchored in various incompatible theories. The paper suggests that information is signs, and it demonstrates how the concept of information can be understood within C.S. Peirce's phenomenologically rooted semiotic. Hence, from there, certain ontological conditions as well epistemological consequences of the information concept can be deduced. Findings The paper argues that an understanding of information, as either objective or subjective/discursive, leads to either objective reductionism and signal processing, that fails to explain how information becomes meaningful at all, or conversely, information is understood only relative to subjective/discursive intentions, agendas, etc. To overcome the limitations of defining information as either objective or subjective/discursive, a semiotic analysis shows that information understood as signs is consistently sensitive to both objective and subjective/discursive features of information. It is consequently argued that information as concept should be defined in relation to ontological conditions having certain epistemological consequences. Originality/value The paper presents an analytical framework, derived from semiotics, that adds to the developments of the philosophical dimensions of information within LIS.
    Theme
    Information
  20. Friedman, A.; Thellefsen, M.: Concept theory and semiotics in knowledge organization (2011) 0.00
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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.