• 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