Search (1 results, page 1 of 1)

  • × author_ss:"Marzano, G."
  • × language_ss:"i"
  • × type_ss:"a"
  1. Marzano, G.: Introduzione alla teoria degli insiemi fuzzy (1992) 0.01
    0.011030885 = product of:
      0.049638983 = sum of:
        0.016935252 = weight(_text_:of in 3117) [ClassicSimilarity], result of:
          0.016935252 = score(doc=3117,freq=8.0), product of:
            0.061262865 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03917671 = queryNorm
            0.27643585 = fieldWeight in 3117, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0625 = fieldNorm(doc=3117)
        0.03270373 = weight(_text_:systems in 3117) [ClassicSimilarity], result of:
          0.03270373 = score(doc=3117,freq=2.0), product of:
            0.12039685 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03917671 = queryNorm
            0.2716328 = fieldWeight in 3117, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0625 = fieldNorm(doc=3117)
      0.22222222 = coord(2/9)
    
    Abstract
    Presents the basic ideas underlying fuzzy set theory, developed by Zadeh in the 1960s, which has important appplications in information retrieval and documentation. A fuzzy information retrieval system is much less restrictive that a Boolean model, since results can be arranged according to degree of similarity. Another application of the theory concerns the use of linguistic quantifiers; this type of solution is well adapted to retrieval systems designed for direct operation by end-users. Illustraes with examples fuzzy set algebra, operation, relationships, logic and reasoning