Search (3 results, page 1 of 1)

  • × author_ss:"Leazer, G.H."
  1. Leazer, G.H.; Smiraglia, R.P.: Bibliographic families in the library catalog : a qualitative analysis and grounded theory (1999) 0.05 
    0.045621287 = product of:
  0.091242574 = sum of:
    0.091242574 = sum of:
      0.05638113 = weight(_text_:network in 107) [ClassicSimilarity], result of:
        0.05638113 = score(doc=107,freq=2.0), product of:
          0.22917621 = queryWeight, product of:
            4.4533744 = idf(docFreq=1398, maxDocs=44218)
            0.05146125 = queryNorm
          0.2460165 = fieldWeight in 107, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.4533744 = idf(docFreq=1398, maxDocs=44218)
            0.0390625 = fieldNorm(doc=107)
      0.034861445 = weight(_text_:22 in 107) [ClassicSimilarity], result of:
        0.034861445 = score(doc=107,freq=2.0), product of:
          0.18020853 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05146125 = queryNorm
          0.19345059 = fieldWeight in 107, 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=107)
  0.5 = coord(1/2)
    Abstract
    Forty-five years have passed since Lubetzky outlined the primary objectives of the catalog, which should facilitate the identification of specific bibliographic entities, and the explicit recoguition of works and relationships amongthem. Still, our catalogs are better designed to identify specific bibliographic entities than they are to guide users among the network of potential related editions and translations of works. In this paper, we seck to examine qualitatively some interesting examples of families of related works, defined as bibliographic families. Although the cases described here were derived from a random sample, this is a qualitative analysis. We selected these bibliographic families for their ability to reveal the strengths and weaknesses of Leazer's model, which incorporates relationship taxonomies by Tillett and Smiraglia Qualitatice analysis is intended to produce on explanation of a phenomenou, particularly an identification of any palterns observed. Patterns observed in qualitative analysis can be used to affirm external observations of the same phenomena; conclusions can contribute to what is knoton as grounded theory-a unique explanation grounded in the phenomenon under study. We arrive at two statements of grounded theory concerning bibliographic families: cataloger-generated implicit maps among works are inadequate, and qualitative analysis suggests the complexity of even the smallest bibliographic families. We conclude that user behavior study is needed to suggest which alternative maps are preferable.
    Date
    10. 9.2000 17:38:22
  2. Leazer, G.H.; Furner, J.: Topological indices of textual identity networks (1999) 0.04 
    0.042285845 = product of:
  0.08457169 = sum of:
    0.08457169 = product of:
      0.16914338 = sum of:
        0.16914338 = weight(_text_:network in 6683) [ClassicSimilarity], result of:
          0.16914338 = score(doc=6683,freq=18.0), product of:
            0.22917621 = queryWeight, product of:
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.05146125 = queryNorm
            0.73804945 = fieldWeight in 6683, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              4.4533744 = idf(docFreq=1398, maxDocs=44218)
              0.0390625 = fieldNorm(doc=6683)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    A textual identity network is a set of documents that share common semantic or linguistic content. For example, the textual identity network of Ben-Hur includes the progenitor work, translations, screen play adaptations, and film performances. A network might also include successively numbered editions, simultaneous editions published in various countries, and other derivative forms. This network expresses how a work evolves over time and through a variety of media. Evolving textual identity can be expressed as a set of relationships among the members of the network. Several taxonomies of intertextual associations have been developed for use in information retrieval systems. The individual documents (books, films, computer files, etc.) contained in a textual identity network can be associated through a number of pairwise relationships, and the network can be studied as a system. This basic pattern makes textual networks ideal candidates for study using network analysis techniques, allowing summary measures that characterize networks. Topological indices provide high-level measures of network structure. This paper concludes on a discussion of how topological indices might be used in document retrieval
  3. Borgman, C.L.; Smart, L.J.; Millwood, K.A.; Finley, J.R.; Champeny, L.; Gilliland, A.J.; Leazer, G.H.: Comparing faculty information seeking in teaching and research : implications for the design of digital libraries (2005) 0.01 
    0.006972289 = product of:
  0.013944578 = sum of:
    0.013944578 = product of:
      0.027889157 = sum of:
        0.027889157 = weight(_text_:22 in 3231) [ClassicSimilarity], result of:
          0.027889157 = score(doc=3231,freq=2.0), product of:
            0.18020853 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05146125 = queryNorm
            0.15476047 = fieldWeight in 3231, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=3231)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Date
    3. 6.2005 20:40:22

Authors

Years

Themes