Search (14 results, page 1 of 1)

  • × theme_ss:"Theorie verbaler Dokumentationssprachen"
  • × type_ss:"a"
  1. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.02 
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    Date
    8.10.2000 11:52:22
  2. Mikacic, M.: Statistical system for subject designation (SSSD) for libraries in Croatia (1996) 0.02 
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    Date
    31. 7.2006 14:22:21
    Source
    Cataloging and classification quarterly. 22(1996) no.1, S.77-93
  3. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.02 
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    Pages
    S.11-22
  4. Melton, J.S.: ¬A use for the techniques of structural linguistics in documentation research (1965) 0.01 
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    Source
    Classification research. Proc. 2nd Int. Study Conf. ... Elsinore, 14.-18.8.1964. Ed.: P. Atherton
  5. Degez, D.: Compatibilité des langages d'indexation mariage, cohabitation ou fusion? : Quelques examples concrèts (1998) 0.01 
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    Date
    1. 8.1996 22:01:00
  6. Dextre Clarke, S.G.: Thesaural relationships (2001) 0.01 
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    Date
    22. 9.2007 15:45:57
  7. Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010) 0.01 
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    Source
    Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
  8. Mazzocchi, F.; Plini, P.: Refining thesaurus relational structure : implications and opportunities (2008) 0.01 
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  9. Maniez, J.: Fusion de banques de donnees documentaires at compatibilite des languages d'indexation (1997) 0.01 
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    Date
    1. 8.1996 22:01:00
  10. Mazzocchi, F.; Tiberi, M.; De Santis, B.; Plini, P.: Relational semantics in thesauri : an overview and some remarks at theoretical and practical levels (2007) 0.01 
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  11. Jia, J.: From data to knowledge : the relationships between vocabularies, linked data and knowledge graphs (2021) 0.01 
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    Date
    22. 1.2021 14:24:32
  12. Farradane, J.E.L.: Fundamental fallacies and new needs in classification (1985) 0.01 
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    Abstract
    The basic fallacy of mechanised information retrieval systems seems to be the often unconscious but apparently implied assumption that the machine can inject meaning into a group of juxtaposed terms although no methods of conceptual analysis and re-synthesis have been programmed (p. 203). As an example, he suggests considering the slight but vital differences in the meaning of the word "of" in selected examples: swarm of bees house of the mayor House of Lords spectrum of the sun basket of fish meeting of councillors cooking of meat book of the film Farradane's distinctive contribution is his matrix of basic relationships. The rows concern time and memory, in degree of happenstance: coincidentally, occasionally, or always. The columns represent degree of the "powers of discrimination": occurring together, linked by common elements only, or standing alone. To make these relationships easily managed, he used symbols for each of the nine kinds - "symbols found an every typewriter": /O (Theta) /* /; /= /+ /( /) /_ /: Farradane has maintained his basic insights to the present day. Though he has gone an to do other kinds of research in classification, his work indicates that he still believes that "the primary task ... is that of establishing satisfactory and enduring principles of subject analysis, or classification" (p. 208).
  13. Khoo, S.G.; Na, J.-C.: Semantic relations in information science (2006) 0.01 
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    Abstract
    This chapter examines the nature of semantic relations and their main applications in information science. The nature and types of semantic relations are discussed from the perspectives of linguistics and psychology. An overview of the semantic relations used in knowledge structures such as thesauri and ontologies is provided, as well as the main techniques used in the automatic extraction of semantic relations from text. The chapter then reviews the use of semantic relations in information extraction, information retrieval, question-answering, and automatic text summarization applications. Concepts and relations are the foundation of knowledge and thought. When we look at the world, we perceive not a mass of colors but objects to which we automatically assign category labels. Our perceptual system automatically segments the world into concepts and categories. Concepts are the building blocks of knowledge; relations act as the cement that links concepts into knowledge structures. We spend much of our lives identifying regular associations and relations between objects, events, and processes so that the world has an understandable structure and predictability. Our lives and work depend on the accuracy and richness of this knowledge structure and its web of relations. Relations are needed for reasoning and inferencing. Chaffin and Herrmann (1988b, p. 290) noted that "relations between ideas have long been viewed as basic to thought, language, comprehension, and memory." Aristotle's Metaphysics (Aristotle, 1961; McKeon, expounded on several types of relations. The majority of the 30 entries in a section of the Metaphysics known today as the Philosophical Lexicon referred to relations and attributes, including cause, part-whole, same and opposite, quality (i.e., attribute) and kind-of, and defined different types of each relation. Hume (1955) pointed out that there is a connection between successive ideas in our minds, even in our dreams, and that the introduction of an idea in our mind automatically recalls an associated idea. He argued that all the objects of human reasoning are divided into relations of ideas and matters of fact and that factual reasoning is founded on the cause-effect relation. His Treatise of Human Nature identified seven kinds of relations: resemblance, identity, relations of time and place, proportion in quantity or number, degrees in quality, contrariety, and causation. Mill (1974, pp. 989-1004) discoursed on several types of relations, claiming that all things are either feelings, substances, or attributes, and that attributes can be a quality (which belongs to one object) or a relation to other objects.
    Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.
  14. Mooers, C.N.: ¬The indexing language of an information retrieval system (1985) 0.01 
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    Footnote
    Original in: Information retrieval today: papers presented at an Institute conducted by the Library School and the Center for Continuation Study, University of Minnesota, Sept. 19-22, 1962. Ed. by Wesley Simonton. Minneapolis, Minn.: The Center, 1963. S.21-36.

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