The Growing Hierarchical Self-Organizing Map

نویسندگان

  • Michael Dittenbach
  • Dieter Merkl
  • Andreas Rauber
چکیده

In this paper we present the growing hierarchical self-organizing map . This dynamically growing neural network model evolves into a hierarchical structure according to the requirements of the input data during an unsupervised training process. We demonstrate the benefits of this novel neural network model by organizing a real-world document collection according to their similarities.

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تاریخ انتشار 2000