An alternative to dealing with high dimension data may be to reduce the dimensionality of the data representation.
linear algebra dimensionality reduction methods like singular value decomposition have been adopted by (Choi et al., 2001;Popescu-Belis et al., 2004) in Latent Semantic Analysis (LSA) for the task of thematic segmentation.