Search (2 results, page 1 of 1)

  • × theme_ss:"Konzeption und Anwendung des Prinzips Thesaurus"
  • × theme_ss:"Visualisierung"
  • × type_ss:"a"
  1. Pfeffer, M.; Eckert, K.; Stuckenschmidt, H.: Visual analysis of classification systems and library collections (2008) 0.01
    0.011426046 = product of:
      0.022852091 = sum of:
        0.022852091 = product of:
          0.034278136 = sum of:
            0.009313605 = weight(_text_:a in 317) [ClassicSimilarity], result of:
              0.009313605 = score(doc=317,freq=6.0), product of:
                0.052761257 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.045758117 = queryNorm
                0.17652355 = fieldWeight in 317, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0625 = fieldNorm(doc=317)
            0.02496453 = weight(_text_:h in 317) [ClassicSimilarity], result of:
              0.02496453 = score(doc=317,freq=2.0), product of:
                0.113683715 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045758117 = queryNorm
                0.21959636 = fieldWeight in 317, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0625 = fieldNorm(doc=317)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    In this demonstration we present a visual analysis approach that addresses both developers and users of hierarchical classification systems. The approach supports an intuitive understanding of the structure and current use in relation to a specific collection. We will also demonstrate its application for the development and management of library collections.
    Type
    a
  2. Eckert, K.; Pfeffer, M.; Stuckenschmidt, H.: Assessing thesaurus-based annotations for semantic search applications (2008) 0.01
    0.011122987 = product of:
      0.022245973 = sum of:
        0.022245973 = product of:
          0.03336896 = sum of:
            0.011524997 = weight(_text_:a in 1528) [ClassicSimilarity], result of:
              0.011524997 = score(doc=1528,freq=12.0), product of:
                0.052761257 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.045758117 = queryNorm
                0.21843673 = fieldWeight in 1528, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1528)
            0.021843962 = weight(_text_:h in 1528) [ClassicSimilarity], result of:
              0.021843962 = score(doc=1528,freq=2.0), product of:
                0.113683715 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045758117 = queryNorm
                0.19214681 = fieldWeight in 1528, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1528)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    Statistical methods for automated document indexing are becoming an alternative to the manual assignment of keywords. We argue that the quality of the thesaurus used as a basis for indexing in regard to its ability to adequately cover the contents to be indexed and as a basis for the specific indexing method used is of crucial importance in automatic indexing. We present an interactive tool for thesaurus evaluation that is based on a combination of statistical measures and appropriate visualisation techniques that supports the detection of potential problems in a thesaurus. We describe the methods used and show that the tool supports the detection and correction of errors, leading to a better indexing result.
    Type
    a