WWW-Newsgroup-Document Clustering by Means of Dynamic Self-organizing Neural Networks

Authors:
Marian B. Gorzałczany;Filip Rudziński
Affiliations:
Department of Electrical and Computer Engineering, Kielce University of Technology, Kielce, Poland 25-314;Department of Electrical and Computer Engineering, Kielce University of Technology, Kielce, Poland 25-314
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

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-Newsnewsgroups) 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.