White, H.D.; Lin, X.; McCain, K.W.: Two modes of automated domain analysis : multidimensional scaling vs. Kohonen feature mapping of information science authors (1998)
0.01
0.012048556 = product of:
0.042169943 = sum of:
0.015536481 = weight(_text_:information in 143) [ClassicSimilarity], result of:
0.015536481 = score(doc=143,freq=6.0), product of:
0.066068366 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.037635546 = queryNorm
0.23515764 = fieldWeight in 143, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0546875 = fieldNorm(doc=143)
0.026633464 = weight(_text_:retrieval in 143) [ClassicSimilarity], result of:
0.026633464 = score(doc=143,freq=2.0), product of:
0.11384433 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.037635546 = queryNorm
0.23394634 = fieldWeight in 143, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=143)
0.2857143 = coord(2/7)
- Abstract
- This paper shows that, given co-citation data, Kohonen feature mapping produces results quite similar to those of multidimensional scaling, the traditional mode for computer-assisted mapping of intellectual domains. It further presents a Kohonen feature map based on author co-citation data that links author names to information about them on the World Wide Web. The results bear on a goal for present-day information science: the integration of computerized bibliometrics with document retrieval