Search (13 results, page 1 of 1)

  • × author_ss:"Green, R."
  1. Green, R.: Relational aspects of subject authority control : the contributions of classificatory structure (2015) 0.05
    0.048659198 = product of:
      0.097318396 = sum of:
        0.097318396 = sum of:
          0.062250152 = weight(_text_:language in 2282) [ClassicSimilarity], result of:
            0.062250152 = score(doc=2282,freq=4.0), product of:
              0.2030952 = queryWeight, product of:
                3.9232929 = idf(docFreq=2376, maxDocs=44218)
                0.051766515 = queryNorm
              0.30650726 = fieldWeight in 2282, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.9232929 = idf(docFreq=2376, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2282)
          0.03506824 = weight(_text_:22 in 2282) [ClassicSimilarity], result of:
            0.03506824 = score(doc=2282,freq=2.0), product of:
              0.18127751 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.051766515 = queryNorm
              0.19345059 = fieldWeight in 2282, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.0390625 = fieldNorm(doc=2282)
      0.5 = coord(1/2)
    
    Abstract
    The structure of a classification system contributes in a variety of ways to representing semantic relationships between its topics in the context of subject authority control. We explore this claim using the Dewey Decimal Classification (DDC) system as a case study. The DDC links its classes into a notational hierarchy, supplemented by a network of relationships between topics, expressed in class descriptions and in the Relative Index (RI). Topics/subjects are expressed both by the natural language text of the caption and notes (including Manual notes) in a class description and by the controlled vocabulary of the RI's alphabetic index, which shows where topics are treated in the classificatory structure. The expression of relationships between topics depends on paradigmatic and syntagmatic relationships between natural language terms in captions, notes, and RI terms; on the meaning of specific note types; and on references recorded between RI terms. The specific means used in the DDC for capturing hierarchical (including disciplinary), equivalence and associative relationships are surveyed.
    Date
    8.11.2015 21:27:22
  2. Green, R.: ¬The expression of syntagmatic relationships in indexing : are frame-based index languages the answer? (1992) 0.02
    0.017607002 = product of:
      0.035214003 = sum of:
        0.035214003 = product of:
          0.07042801 = sum of:
            0.07042801 = weight(_text_:language in 2093) [ClassicSimilarity], result of:
              0.07042801 = score(doc=2093,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.34677336 = fieldWeight in 2093, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0625 = fieldNorm(doc=2093)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The frame structure matches the profile of features desirable in a syntagmatic relationship system and should be incorporated as the basic structural unit in index languages. The construction of frame-based index languages is discussed. Selected findings based on the case study analysis of implementing a New Testament-oriented frame-based indexing language are presented
  3. Green, R.: Attribution and relationality (1998) 0.02
    0.017607002 = product of:
      0.035214003 = sum of:
        0.035214003 = product of:
          0.07042801 = sum of:
            0.07042801 = weight(_text_:language in 6425) [ClassicSimilarity], result of:
              0.07042801 = score(doc=6425,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.34677336 = fieldWeight in 6425, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0625 = fieldNorm(doc=6425)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The paper examines the role of attributes within entity-relationship-based conceptual modeling, investigating the interplay between attributes and relationships within (1) data modeling and (2) natural language use. Attribution is found to be an important relationship type. The lack of distinctiveness between attributes and relationships leads to a re-examination of how hierarchy should be treated in both the practice and theory of knowledge organization
  4. Green, R.; Fraser, L.: Patterns in verbal polysemy (2004) 0.02
    0.017607002 = product of:
      0.035214003 = sum of:
        0.035214003 = product of:
          0.07042801 = sum of:
            0.07042801 = weight(_text_:language in 2621) [ClassicSimilarity], result of:
              0.07042801 = score(doc=2621,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.34677336 = fieldWeight in 2621, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0625 = fieldNorm(doc=2621)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Although less well studied than noun polysemy, verb polysemy affects both natural language and controlled vocabulary searching. This paper reports the preliminary conclusions of an empirical investigation of the semantic relationships between ca. 600 verb sense pairs in English, illustrating six classes of semantic relationships that account for a significant proportion of verbal polysemy.
  5. Green, R.: ¬The expression of conceptual syntagmatic relationships : a comparative survey (1995) 0.02
    0.015406125 = product of:
      0.03081225 = sum of:
        0.03081225 = product of:
          0.0616245 = sum of:
            0.0616245 = weight(_text_:language in 4475) [ClassicSimilarity], result of:
              0.0616245 = score(doc=4475,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.30342668 = fieldWeight in 4475, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4475)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The expression of conceptual syntagmatic relationships in document retrieval systems holds out hope for both increased discrimination generally and increased recall in certain contexts. Such relationships require both a structured inventory of relationships. Examines the means of expressing these. The expression of conceptual syntagmatic relationships must comply with criteria of systematicity, complexity, efficiency and naturalness. Unfortunately, the complex interaction of natural language expression based on lexicalization, word order, function words, and morphosyntactic cases causes failure regarding systematicity. Most methods of expressing conceptual syntagmatic relationships, e.g. term co occurrence techniques, links and role indicators, fail to comply with this and other of the criteria. Only gestalt structures simultaneously representing relationships, participants and roles conform fully to the critical checklist
  6. Green, R.: Relationships in knowledge organization (2008) 0.02
    0.015406125 = product of:
      0.03081225 = sum of:
        0.03081225 = product of:
          0.0616245 = sum of:
            0.0616245 = weight(_text_:language in 2135) [ClassicSimilarity], result of:
              0.0616245 = score(doc=2135,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.30342668 = fieldWeight in 2135, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=2135)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Relationships that interconnect entity classes of import to knowledge organization (knowledge, documents, concepts, beings, information needs, language) include both non-subject bibliographic relationships (document-to-document relationships, responsibility relationships) and conceptual content relationships (subject relationships, relevance relationships). While the MARC format allows the recording of most bibliographic relationships, many of them are not expressed systematically. Conceptual content relationships include, in turn, interconcept and intraconcept relationships. The expression of interconcept relationships is covered by standard thesaural relationships, which typically do not distinguish fully between the underlying lexical relationship types. The full expression of complex intraconcept relationships includes indication of the basic nature of the relationship (including a set of semantic roles), the set of entities that participate in the relationship, and a mapping between participants and semantic roles. Knowledge organization schemes seldom express these relationships fully.
  7. Green, R.: Making visible hidden relationships in the Dewey Decimal Classification : how relative index terms relate to DDC classes (2008) 0.02
    0.015406125 = product of:
      0.03081225 = sum of:
        0.03081225 = product of:
          0.0616245 = sum of:
            0.0616245 = weight(_text_:language in 2236) [ClassicSimilarity], result of:
              0.0616245 = score(doc=2236,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.30342668 = fieldWeight in 2236, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=2236)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Content
    Relative Index (RI) terms in the Dewey Decimal Classification (DDC) system correspond to concepts that either approximate the whole of the class they index or that are in standing room there. DDC conventions and shallow natural language processing are used to determine automatically whether specific RI terms approximate the whole of or are in standing room in the classes they index. Approximately three-quarters of all RI terms are processed by the techniques described.
  8. Green, R.; Panzer, M.: ¬The ontological character of classes in the Dewey Decimal Classification 0.02
    0.015406125 = product of:
      0.03081225 = sum of:
        0.03081225 = product of:
          0.0616245 = sum of:
            0.0616245 = weight(_text_:language in 3530) [ClassicSimilarity], result of:
              0.0616245 = score(doc=3530,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.30342668 = fieldWeight in 3530, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=3530)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
  9. Green, R.: See-also relationships in the Dewey Decimal Classification (2011) 0.02
    0.015406125 = product of:
      0.03081225 = sum of:
        0.03081225 = product of:
          0.0616245 = sum of:
            0.0616245 = weight(_text_:language in 4615) [ClassicSimilarity], result of:
              0.0616245 = score(doc=4615,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.30342668 = fieldWeight in 4615, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4615)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    This paper investigates the semantics of topical, associative see-also relationships in schedule and table entries of the Dewey Decimal Classification (DDC) system. Based on the see-also relationships in a random sample of 100 classes containing one or more of these relationships, a semi-structured inventory of sources of see-also relationships is generated, of which the most important are lexical similarity, complementarity, facet difference, and relational configuration difference. The premise that see-also relationships based on lexical similarity may be language-specific is briefly examined. The paper concludes with recommendations on the continued use of see-also relationships in the DDC.
  10. Green, R.: Topical relevance relationships : 1: why topic matching fails (1995) 0.01
    0.01320525 = product of:
      0.0264105 = sum of:
        0.0264105 = product of:
          0.052821 = sum of:
            0.052821 = weight(_text_:language in 3722) [ClassicSimilarity], result of:
              0.052821 = score(doc=3722,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.26008 = fieldWeight in 3722, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3722)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Presents conceptual background. Since topicality is a major factor in relevance, it is crucial to identify the range of relationship types that occur between the topics of user needs and the topics of texts relevant to those needs. Assumes that a single relationship type obtains i.e. that the 2 topics match. Evidence from the analysis of recall failures, citation analysis, and knowledge synthesis suggests otherwise: topical relevance relationships are not limited to topic matching relationships; to the contrary, in certain circumstances they are quite likely not to be matching relationships. Relationships are 1 of the 2 fundamental components of human conceptual systems. Attempts to classify them usually accept a distinction between relationships that occur by virute of the combination of component units (syntagmatic relationships) and relationships that are bulit into the language system (paradigmatic relationships). Given the variety of relationship types previously identified, empirical research is needed to determine the subset that actually account for topical relevance
  11. Green, R.: Conceptual universals in knowledge organization and representation (2003) 0.01
    0.01320525 = product of:
      0.0264105 = sum of:
        0.0264105 = product of:
          0.052821 = sum of:
            0.052821 = weight(_text_:language in 2629) [ClassicSimilarity], result of:
              0.052821 = score(doc=2629,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.26008 = fieldWeight in 2629, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2629)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Within the overall conference theme-integration of knowledge across boundaries-an important subtheme is universality: Where universals of knowledge organization and representation exist, knowledge integration is more likely. Thus, knowledge of conceptual universals should inform efforts at knowledge integration. In this paper, natural language is used as a model for exploring conceptual universals, since the phenomenon of translating between languages validates, but also circumscribes, the existence of semantic and lexical universals. The paper explores a representative inventory of semantic and lexical universals that should be accounted for in knowledge organization and representation systems, especially those that aim to be comprehensive.
  12. Green, R.: Facet detection using WorldCat and WordNet (2014) 0.01
    0.012273884 = product of:
      0.024547769 = sum of:
        0.024547769 = product of:
          0.049095538 = sum of:
            0.049095538 = weight(_text_:22 in 1419) [ClassicSimilarity], result of:
              0.049095538 = score(doc=1419,freq=2.0), product of:
                0.18127751 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.051766515 = queryNorm
                0.2708308 = fieldWeight in 1419, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1419)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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
  13. Green, R.; Panzer, M.: Relations in the notational hierarchy of the Dewey Decimal Classification (2011) 0.01
    0.011004375 = product of:
      0.02200875 = sum of:
        0.02200875 = product of:
          0.0440175 = sum of:
            0.0440175 = weight(_text_:language in 4823) [ClassicSimilarity], result of:
              0.0440175 = score(doc=4823,freq=2.0), product of:
                0.2030952 = queryWeight, product of:
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.051766515 = queryNorm
                0.21673335 = fieldWeight in 4823, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9232929 = idf(docFreq=2376, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4823)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    As part of a larger assessment of relationships in the Dewey Decimal Classification (DDC) system, this study investigates the semantic nature of relationships in the DDC notational hierarchy. The semantic relationship between each of a set of randomly selected classes and its parent class in the notational hierarchy is examined against a set of relationship types (specialization, class-instance, several flavours of whole-part).The analysis addresses the prevalence of specific relationship types, their lexical expression, difficulties encountered in assigning relationship types, compatibility of relationships found in the DDC with those found in other knowledge organization systems (KOS), and compatibility of relationships found in the DDC with those in a shared formalism like the Web Ontology Language (OWL). Since notational hierarchy is an organizational mechanism shared across most classification schemes and is often considered to provide an easy solution for ontological transformation of a classification system, the findings of the study are likely to generalize across classification schemes with respect to difficulties that might be encountered in such a transformation process.