Search (2 results, page 1 of 1)

  • × author_ss:"Bergmann, R."
  • × theme_ss:"Case Based Reasoning"
  1. Althoff, K.-D.; Wess, S.; Manago, M.; Bergmann, R.; Maurer, F.; Auriol, E.; Conruyt, N.; Traphöner, R.; Bräuer, M.; Dittrich, S.: Induction and case-based reasoning for classification tasks (1994) 0.04 
    0.037850365 = product of:
  0.15140146 = sum of:
    0.102602884 = weight(_text_:case in 7744) [ClassicSimilarity], result of:
      0.102602884 = score(doc=7744,freq=6.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.58892816 = fieldWeight in 7744, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7744)
    0.048798583 = weight(_text_:studies in 7744) [ClassicSimilarity], result of:
      0.048798583 = score(doc=7744,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.30860704 = fieldWeight in 7744, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7744)
  0.25 = coord(2/8)
    Abstract
    We present 2 techniques for reasoning from cases to solve classification tasks: induction and case-based reasoning. We contrast the 2 technologies (that are often confused) and show how they complement each other. Based on this, we describe how they are integrated in one single platform for reasoning from cases: the INRECA system
    Series
    Studies in classification, data analysis, and knowledge organization
    Theme
    Case Based Reasoning
  2. Veleso, M.; Munoz-Avila, H.; Bergmann, R.: Case-based planning : selected methods and systems (1996) 0.03 
    0.025911141 = product of:
  0.20728913 = sum of:
    0.20728913 = weight(_text_:case in 7477) [ClassicSimilarity], result of:
      0.20728913 = score(doc=7477,freq=12.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        1.1898146 = fieldWeight in 7477, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.078125 = fieldNorm(doc=7477)
  0.125 = coord(1/8)
    Abstract
    Describes a framework for case based planning based on the case based reasoning process model. It covers work based on the integration of a generative problem solver with a case based component. Describes case based reasoning planning systems developed at the Carnegie Mellon University, Pittsburgh
    Theme
    Case Based Reasoning

Authors