# Ideas to create better self-organized maps using textual data; issues dealing with highly sparse data

I have a term-document frequency matrix which is thus high-dimensional and very sparse. Whenever I generate SOMs in the "Kohonen" package in R I get one node dominating the others no matter which topology or learning rate I use. Is there a clear way of dealing with high-dimensional sparse data because this is effecting the topology of the network in that one node is dominating the rest.