Recent Advances with the Growing Hierarchical Self-Organizing Map

  • Michael Dittenbach
  • Andreas Rauber
  • Dieter Merkl

Abstract

We present our recent work on the Growing Hierarchical Self-Organizing Map, a dynamically growing neural network model which evolves into a hierarchical structure according to the necessities of the input data during an unsupervised training process. The benefits of this novel architecture are shown by organizing a real-world document collection according to semantic similarities.

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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Michael Dittenbach
    • 1
  • Andreas Rauber
    • 2
  • Dieter Merkl
    • 2
  1. 1.E-Commerce Competence Center - EC3WienAustria
  2. 2.Institut für Softwaretechnik, Technische Universität WienWienAustria

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