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
         
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
         
        
            Conference_Location : 
Seattle, WA
         
        
            Print_ISBN : 
0-7803-0164-1
         
        
        
            DOI : 
10.1109/IJCNN.1991.155602