Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering

We present a novel approach to the growing neural gas (GNG) based clustering of the high-dimensional text data. We enhance our Contextual GNG models (proposed previously to shift the majority of calculations to context-sensitive, local sub-graphs and local sub-spaces and so to reduce computational complexity) by developing a new, histogram-based method for incremental model adaptation and evaluation of its stability.