Search (1 results, page 1 of 1)

  • × author_ss:"Benoit, G."
  • × theme_ss:"Computerlinguistik"
  • × year_i:[2000 TO 2010}
  1. Benoit, G.: Data discretization for novel relationship discovery in information retrieval (2002) 0.02
    0.015685532 = product of:
      0.05489936 = sum of:
        0.046192586 = weight(_text_:g in 5197) [ClassicSimilarity], result of:
          0.046192586 = score(doc=5197,freq=2.0), product of:
            0.13914184 = queryWeight, product of:
              3.7559474 = idf(docFreq=2809, maxDocs=44218)
              0.03704574 = queryNorm
            0.331982 = fieldWeight in 5197, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.7559474 = idf(docFreq=2809, maxDocs=44218)
              0.0625 = fieldNorm(doc=5197)
        0.008706774 = weight(_text_:a in 5197) [ClassicSimilarity], result of:
          0.008706774 = score(doc=5197,freq=8.0), product of:
            0.04271548 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.03704574 = queryNorm
            0.20383182 = fieldWeight in 5197, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=5197)
      0.2857143 = coord(2/7)
    
    Abstract
    A sample of 600 Dialog and Swiss-Prot full text records in genetics and molecular biology were parsed and term frequencies calculated to provide data for a test of Benoit's visualization model for retrieval. A retrieved set is displayed graphically allowing for manipulation of document and concept relationships in real time, which hopefully will reveal unanticipated relationships.
    Type
    a