Search (3 results, page 1 of 1)

  • × author_ss:"Green, R."
  • × theme_ss:"Wissensrepräsentation"
  1. Green, R.: WordNet (2009) 0.01
    0.0050137267 = product of:
      0.035096087 = sum of:
        0.014125523 = weight(_text_:information in 4696) [ClassicSimilarity], result of:
          0.014125523 = score(doc=4696,freq=8.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.27153665 = fieldWeight in 4696, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4696)
        0.020970564 = weight(_text_:retrieval in 4696) [ClassicSimilarity], result of:
          0.020970564 = score(doc=4696,freq=2.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.23394634 = fieldWeight in 4696, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4696)
      0.14285715 = coord(2/14)
    
    Abstract
    WordNet, a lexical database for English, is organized around semantic and lexical relationships between synsets, concepts represented by sets of synonymous word senses. Offering reasonably comprehensive coverage of the nouns, verbs, adjectives, and adverbs of general English, WordNet is a widely used resource for dealing with the ambiguity that arises from homonymy, polysemy, and synonymy. WordNet is used in many information-related tasks and applications (e.g., word sense disambiguation, semantic similarity, lexical chaining, alignment of parallel corpora, text segmentation, sentiment and subjectivity analysis, text classification, information retrieval, text summarization, question answering, information extraction, and machine translation).
    Source
    Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
  2. Green, R.: See-also relationships in the Dewey Decimal Classification (2011) 0.00
    0.0014978976 = product of:
      0.020970564 = sum of:
        0.020970564 = weight(_text_:retrieval in 4615) [ClassicSimilarity], result of:
          0.020970564 = score(doc=4615,freq=2.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.23394634 = fieldWeight in 4615, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4615)
      0.071428575 = coord(1/14)
    
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. Green, R.; Panzer, M.: Relations in the notational hierarchy of the Dewey Decimal Classification (2011) 0.00
    0.001245368 = product of:
      0.017435152 = sum of:
        0.017435152 = weight(_text_:web in 4823) [ClassicSimilarity], result of:
          0.017435152 = score(doc=4823,freq=2.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.18028519 = fieldWeight in 4823, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4823)
      0.071428575 = coord(1/14)
    
    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.