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  • × author_ss:"Green, R."
  1. Green, R.; Panzer, M.: ¬The ontological character of classes in the Dewey Decimal Classification 0.02
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    Abstract
    Classes in the Dewey Decimal Classification (DDC) system function as neighborhoods around focal topics in captions and notes. Topical neighborhoods are generated through specialization and instantiation, complex topic synthesis, index terms and mapped headings, hierarchical force, rules for choosing between numbers, development of the DDC over time, and use of the system in classifying resources. Implications of representation using a formal knowledge representation language are explored.
  2. Green, R.: Topical relevance relationships : 2: an exploratory study and preliminary typology (1995) 0.02
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    Abstract
    The assumption of topic matching between user needs and texts topically relevant to those needs is often erroneous. Reports an emprical investigantion of the question 'what relationship types actually account for topical relevance'? In order to avoid the bias to topic matching search strategies, user needs are back generated from a randomly selected subset of the subject headings employed in a user oriented topical concordance. The corresponding relevant texts are those indicated in the concordance under the subject heading. Compares the topics of the user needs with the topics of the relevant texts to determine the relationships between them. Topical relevance relationships include a large variety of relationships, only some of which are matching relationships. Others are examples of paradigmatic or syntagmatic relationships. There appear to be no constraints on the kinds of relationships that can function as topical relevance relationships. They are distinguishable from other types of relationships only on functional grounds
  3. Green, R.: Facet analysis and semantic frames (2017) 0.01
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    Abstract
    Various fields, each with its own theories, techniques, and tools, are concerned with identifying and representing the conceptual structure of specific knowledge domains. This paper compares facet analysis, an analytic technique coming out of knowledge organization (especially as undertaken by members of the Classification Research Group (CRG)), with semantic frame analysis, an analytic technique coming out of lexical semantics (especially as undertaken by the developers of Frame-Net) The investigation addresses three questions: 1) how do CRG-style facet analysis and semantic frame analysis characterize the conceptual structures that they identify?; 2) how similar are the techniques they use?; and, 3) how similar are the conceptual structures they produce? Facet analysis is concerned with the logical categories underlying the terminology of an entire field, while semantic frame analysis is concerned with the participant-and-prop structure manifest in sentences about a type of situation or event. When their scope of application is similar, as, for example, in the areas of the performing arts or education, the resulting facets and semantic frame elements often bear striking resemblance, without being the same; facets are more often expressed as semantic types, while frame elements are more often expressed as roles.
  4. Green, R.: Facet detection using WorldCat and WordNet (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
  5. Green, R.: Relational aspects of subject authority control : the contributions of classificatory structure (2015) 0.00
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    Date
    8.11.2015 21:27:22