Marzano, G.: Introduzione alla teoria degli insiemi fuzzy (1992)
0.00
4.8283124E-4 = product of:
0.007242468 = sum of:
0.004988801 = weight(_text_:in in 3117) [ClassicSimilarity], result of:
0.004988801 = score(doc=3117,freq=4.0), product of:
0.029340398 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.021569785 = queryNorm
0.17003182 = fieldWeight in 3117, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.0625 = fieldNorm(doc=3117)
0.002253667 = weight(_text_:s in 3117) [ClassicSimilarity], result of:
0.002253667 = score(doc=3117,freq=2.0), product of:
0.023451481 = queryWeight, product of:
1.0872376 = idf(docFreq=40523, maxDocs=44218)
0.021569785 = queryNorm
0.09609913 = fieldWeight in 3117, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.0872376 = idf(docFreq=40523, maxDocs=44218)
0.0625 = fieldNorm(doc=3117)
0.06666667 = coord(2/30)
- 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
- Source
- L'Indicizzazione. 2(1992) no.2, S.33-58
