Interpreting the Kohonen self-organizing feature map using contiguity-constrained clustering

An interpretation phase is proposed, to complement usage of the Kohonen self-organizing feature map (SOFM) method. This segments the SOFM output, using an agglomerative contiguity-constrained clustering method. We discuss why such a clustering method, which respects contiguity information, should be used. The contiguity-constrained clustering method implemented uses array operations as far as possible, and is thus quite efficient. An application to an astronomical catalog of about a quarter million objects is presented.