Search (3 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Konzeption und Anwendung des Prinzips Thesaurus"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Spiteri, L.F.: ¬The essential elements of faceted thesauri (1999) 0.09
    0.08781542 = product of:
      0.13172312 = sum of:
        0.10759281 = weight(_text_:systematic in 5362) [ClassicSimilarity], result of:
          0.10759281 = score(doc=5362,freq=2.0), product of:
            0.28397155 = queryWeight, product of:
              5.715473 = idf(docFreq=395, maxDocs=44218)
              0.049684696 = queryNorm
            0.3788859 = fieldWeight in 5362, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.715473 = idf(docFreq=395, maxDocs=44218)
              0.046875 = fieldNorm(doc=5362)
        0.024130303 = product of:
          0.048260607 = sum of:
            0.048260607 = weight(_text_:indexing in 5362) [ClassicSimilarity], result of:
              0.048260607 = score(doc=5362,freq=2.0), product of:
                0.19018644 = queryWeight, product of:
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.049684696 = queryNorm
                0.2537542 = fieldWeight in 5362, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5362)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Abstract
    The goal of this study is to evaluate, compare, and contrast how facet analysis is used to construct the systematic or faceted displays of a selection of information retrieval thesauri. More specifically, the study seeks to examine which principles of facet analysis are used in the thesauri, and the extent to which different thesauri apply these principles in the same way. A measuring instrument was designed for the purpose of evaluating the structure of faceted thesauri. This instrument was applied to fourteen faceted information retrieval thesauri. The study reveals that the thesauri do not share a common definition of what constitutes a facet. In some cases, the thesauri apply both enumerative-style classification and facet analysis to arrange their indexing terms. A number of the facets used in the thesauri are not homogeneous or mutually exclusive. The principle of synthesis is used in only 50% of the thesauri, and no one citation order is used consistently by the thesauri.
  2. Chen, H.; Martinez, J.; Kirchhoff, A.; Ng, T.D.; Schatz, B.R.: Alleviating search uncertainty through concept associations : automatic indexing, co-occurence analysis, and parallel computing (1998) 0.02
    0.016086869 = product of:
      0.048260607 = sum of:
        0.048260607 = product of:
          0.09652121 = sum of:
            0.09652121 = weight(_text_:indexing in 5202) [ClassicSimilarity], result of:
              0.09652121 = score(doc=5202,freq=8.0), product of:
                0.19018644 = queryWeight, product of:
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.049684696 = queryNorm
                0.5075084 = fieldWeight in 5202, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5202)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    In this article, we report research on an algorithmic approach to alleviating search uncertainty in a large information space. Grounded on object filtering, automatic indexing, and co-occurence analysis, we performed a large-scale experiment using a parallel supercomputer (SGI Power Challenge) to analyze 400.000+ abstracts in an INSPEC computer engineering collection. Two system-generated thesauri, one based on a combined object filtering and automatic indexing method, and the other based on automatic indexing only, were compaed with the human-generated INSPEC subject thesaurus. Our user evaluation revealed that the system-generated thesauri were better than the INSPEC thesaurus in 'concept recall', but in 'concept precision' the 3 thesauri were comparable. Our analysis also revealed that the terms suggested by the 3 thesauri were complementary and could be used to significantly increase 'variety' in search terms the thereby reduce search uncertainty
  3. Jarvelin, K.: ¬A deductive data model for thesaurus navigation and query expansion (1996) 0.01
    0.01072458 = product of:
      0.032173738 = sum of:
        0.032173738 = product of:
          0.064347476 = sum of:
            0.064347476 = weight(_text_:indexing in 5625) [ClassicSimilarity], result of:
              0.064347476 = score(doc=5625,freq=2.0), product of:
                0.19018644 = queryWeight, product of:
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.049684696 = queryNorm
                0.3383389 = fieldWeight in 5625, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.8278677 = idf(docFreq=2614, maxDocs=44218)
                  0.0625 = fieldNorm(doc=5625)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    Describes a deductive data model based on 3 abstraction levels for representing vocabularies for information retrieval: conceptual level; expression level; and occurrence level. The proposed data model can be used for the representation and navigation of indexing and retrieval thesauri and as a vocabulary source for concept based query expansion in heterogeneous retrieval environments

Types