DocumentCode :
2746790
Title :
A neural network that learns to do hyphenation
Author :
Fritzke, Bemd ; Nasahl, Christof
Author_Institution :
Inst. fur Math. Maschinen und Datenverarbeitung, Erlangen-Nuernberg Univ., Germany
fYear :
1991
fDate :
8-14 Jul 1991
Abstract :
Summary form only given, as follows. Hyphenation of German words is a highly irregular problem. Existing solutions for automatic hyphenation are not very satisfying. A `sequential network´ was applied to this problem. The training algorithm was standard backpropagation. The network was trained with a collection of 1000 German words together with their correct hyphenation. In subsequent tests with unknown words, a correctness of 96.8 percent was achieved. Analysis of the simulation results indicates that with further increases of the training data improvements are still possible
Keywords :
learning systems; neural nets; word processing; German words; hyphenation; neural network; sequential network; standard backpropagation; training algorithm; word processing; Analytical models; Associative memory; Backpropagation algorithms; Hilbert space; Interpolation; Kernel; Neural networks; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
Type :
conf
DOI :
10.1109/IJCNN.1991.155602
Filename :
155602
Link To Document :
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