Search (2 results, page 1 of 1)

0.004164351 = product of:
  0.016657405 = sum of:
    0.016657405 = weight(_text_:information in 4679) [ClassicSimilarity], result of:
      0.016657405 = score(doc=4679,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.27153665 = fieldWeight in 4679, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.109375 = fieldNorm(doc=4679)
  0.25 = coord(1/4)

Source

Encyclopedia of library and information science. Vol.63, [=Suppl.26]

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 7437) [ClassicSimilarity], result of:
      0.013461215 = score(doc=7437,freq=4.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 7437, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0625 = fieldNorm(doc=7437)
  0.25 = coord(1/4)

Abstract

Compares the use of 2 adaptive algorithms (genetic algorithms, and neural networks) in clustering hypermedia documents. The clusters allow the user to index into the nodes and find information quickly. The clustering focuses on the user's paths through the hypermedia document and not on the content of the nodes or the structure of the links in the document, thus the clustering reflects the unique relationships each user sees among the nodes. The original hypermedia document remains untouched, and each user has a personalised index into this document

Source

Information systems. 21(1996) no.6, S.459-473