Search (2 results, page 1 of 1)

  • × author_ss:"He, Q."
  • × theme_ss:"Computerlinguistik"
  1. He, Q.: Knowledge discovery through co-word analysis (1999) 0.00 
    0.0017548124 = product of:
  0.010528875 = sum of:
    0.010528875 = weight(_text_:e in 6082) [ClassicSimilarity], result of:
      0.010528875 = score(doc=6082,freq=2.0), product of:
        0.047356583 = queryWeight, product of:
          1.43737 = idf(docFreq=28552, maxDocs=44218)
          0.03294669 = queryNorm
        0.2223318 = fieldWeight in 6082, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.43737 = idf(docFreq=28552, maxDocs=44218)
          0.109375 = fieldNorm(doc=6082)
  0.16666667 = coord(1/6)
    Language
    e
  2. He, Q.: ¬A study of the strength indexes in co-word analysis (2000) 0.00 
    0.0013026106 = product of:
  0.007815664 = sum of:
    0.007815664 = weight(_text_:e in 111) [ClassicSimilarity], result of:
      0.007815664 = score(doc=111,freq=6.0), product of:
        0.047356583 = queryWeight, product of:
          1.43737 = idf(docFreq=28552, maxDocs=44218)
          0.03294669 = queryNorm
        0.16503859 = fieldWeight in 111, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.43737 = idf(docFreq=28552, maxDocs=44218)
          0.046875 = fieldNorm(doc=111)
  0.16666667 = coord(1/6)
    Abstract
    Co-word analysis is a technique for detecting the knowledge structure of scientific literature and mapping the dynamics in a research field. It is used to count the co-occurrences of term pairs, compute the strength between term pairs, and map the research field by inserting terms and their linkages into a graphical structure according to the strength values. In previous co-word studies, there are two indexes used to measure the strength between term pairs in order to identify the major areas in a research field - the inclusion index (I) and the equivalence index (E). This study will conduct two co-word analysis experiments using the two indexes, respectively, and compare the results from the two experiments. The results show, due to the difference in their computation, index I is more likely to identify general subject areas in a research field while index E is more likely to identify subject areas at more specific levels
    Language
    e

Years