The paper presents a clustering technique based on dynamic self-organizing neural networks and its application to a large-scale and highly multidimensional WWW-newsgroup-document clustering problem. The collection of 19 997 documents (e-mail messages of different  Usenet-News newsgroups) available at WWW server of the School of Computer Science, Carnegie Mellon University (www.cs.cmu.edu/ TextLearning/datasets.html) has been the subject of clustering. A broad comparative analysis with nine alternative clustering techniques has also been carried out demonstrating the superiority of the proposed approach in the considered problem.
['Marian B. Gorzałczany', 'Filip Rudziński']
WWW-Newsgroup-Document Clustering by Means of Dynamic Self-organizing Neural Networks