Sabah, G.: Knowledge representation and natural language understanding (1993)
0.01
0.010456172 = product of:
0.041824687 = sum of:
0.041824687 = product of:
0.083649375 = sum of:
0.083649375 = weight(_text_:aspects in 7025) [ClassicSimilarity], result of:
0.083649375 = score(doc=7025,freq=2.0), product of:
0.20938325 = queryWeight, product of:
4.5198684 = idf(docFreq=1308, maxDocs=44218)
0.046325076 = queryNorm
0.39950368 = fieldWeight in 7025, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.5198684 = idf(docFreq=1308, maxDocs=44218)
0.0625 = fieldNorm(doc=7025)
0.5 = coord(1/2)
0.25 = coord(1/4)
- Abstract
- Describes the basic artificial intelligence techniques in linguistic knowledge processing which attempts to get machines to understand natural languages. Focusses on how computing techniques can model the communication process. Briefly examines the theoretical and practical importance of this field. Introduces a sample of theories used to represent linguistic knowledge. Present semantic representations (various logics and semantic networks) and examines pragmatic aspects of communication (of discourse analysis). Describes parsing systems. Addresses architectural issues. Shows why Distributed Artificial Intelligence and reflective systems offers the best framework taking examples from the CARAMEL (Comprehension Automatique de Recites, Apprentissage et Modelisation des Exchanges langagiers)
