Ciganik, M.: Inteligencne indexovanie a inteligencne klasifikacie (1994)
0.01
0.010875943 = product of:
0.0761316 = sum of:
0.0380658 = weight(_text_:classification in 1051) [ClassicSimilarity], result of:
0.0380658 = score(doc=1051,freq=4.0), product of:
0.09562149 = queryWeight, product of:
3.1847067 = idf(docFreq=4974, maxDocs=44218)
0.03002521 = queryNorm
0.39808834 = fieldWeight in 1051, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.1847067 = idf(docFreq=4974, maxDocs=44218)
0.0625 = fieldNorm(doc=1051)
0.0380658 = weight(_text_:classification in 1051) [ClassicSimilarity], result of:
0.0380658 = score(doc=1051,freq=4.0), product of:
0.09562149 = queryWeight, product of:
3.1847067 = idf(docFreq=4974, maxDocs=44218)
0.03002521 = queryNorm
0.39808834 = fieldWeight in 1051, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.1847067 = idf(docFreq=4974, maxDocs=44218)
0.0625 = fieldNorm(doc=1051)
0.14285715 = coord(2/14)
- Abstract
- Examines the shortcomings of traditional indexing and classification methods. Artificial intelligence systems may provide the answer to the problem of improving indexing and classification effectiveness. presents a conceptual modelling method which can be used as a basis for conceptual indexing, i.e. a model of knowledge structures suitable for automatic text analysis and, consequently, for compilation of association thesauri for text databases
