The growing hierarchical self-organizing map
Michael Dittenbach, Dieter Merkl, Andreas Rauber · 2000
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.