DocumentCode :
2302861
Title :
A neural network for supervised learning of natural language grammar
Author :
Archambault, D. ; Bassano, J.-C.
Author_Institution :
LIFO, Orleans Univ., France
fYear :
1994
fDate :
6-9 Nov 1994
Firstpage :
267
Lastpage :
273
Abstract :
Within the framework of the expert information retrieval system, DIALECT 2, we propose a connectionist method for a linguistic morpho-syntactic parser of the French language. The system is based upon a three layered neural network with a recursive sentence structure. This network is in charge of the acquisition of natural language grammatical competence. The learning stage is supervised and distributed into several levels. The learning algorithm uses a measure grounded on an entropic computation. We describe the overall architecture of the system and show the first results obtained with samples made up with sentences from schoolbooks for children who are taught reading
Keywords :
feedforward neural nets; grammars; information retrieval; information retrieval systems; learning (artificial intelligence); natural language interfaces; natural languages; DIALECT 2; French language; connectionist method; entropic computation; information retrieval system; learning algorithm; linguistic morpho-syntactic parsing; natural language grammar; natural language grammatical competence acquisition; reading; recursive sentence structure; schoolbooks; supervised learning; three layered neural network; Computer architecture; Deductive databases; Educational institutions; Entropy; Expert systems; Information analysis; Information retrieval; Natural languages; Neural networks; Supervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-8186-6785-0
Type :
conf
DOI :
10.1109/TAI.1994.346481
Filename :
346481
Link To Document :
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