The ant colony optimization meta-heuristic
New ideas in optimization
Self-Organizing Maps
On Clustering Validation Techniques
Journal of Intelligent Information Systems
A Self-Organizing Network that Can Follow Non-stationary Distributions
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
An immune network for contextual text data clustering
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Towards adaptive web mining: histograms and contexts in text data clustering
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Contextual adaptive clustering of web and text documents with personalization
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Term distribution-based initialization of fuzzy text clustering
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
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In this paper, we focus on the class of graph-based clustering models, such as growing neural gas or idiotypic nets for the purpose of high-dimensional text data clustering. We present a novel approach, which does not require operation on the complex overall graph of clusters, but rather allows to shift majority of effort to context-sensitive, local subgraph and local sub-space processing. Savings of orders of magnitude in processing time and memory can be achieved, while the quality of clusters is improved, as presented experiments demonstrate.