Hierarchical clustering with ART neural networks

This paper introduces the concept of a modular neural network structure, which is capable of clustering input patterns through unsupervised learning, and representing a self-consistent hierarchy of clusters at several levels of specificity. In particular, we use the ART neural network as a building block, and name our architecture SMART (for Self-consistent Modular ART). We also show some experimental results for “proof-of-concept” using the ARTMAP network, that can be seen as an implementation of a two-level SMART network