COMPARISON OF NEURAL NETWORKS USED FOR PROCESSING AND CATEGORIZATION OF CZECH WRITTEN DOCUMENTS

Pavel Mautner, Roman Mouček

2010

Abstract

The Kohonen Self-organizing Feature Map (SOM) has been developed for the clustering of input vectors and for projection of continuous high-dimensional signal to discrete low-dimensional space. The application area, where the map can be also used, is the processing of collections of text documents. The basic principles of the WEBSOM method, a transformation of text information into a real components feature vector and results of documents classification are described in the article. The Carpenter-Grossberg ART-2 neural network, usually used for adaptive vector clustering, was also tested as a document categorization tool. The results achieved by using this network are also presented here.

Paper Citation

in Harvard Style

Mautner P. and Mouček R. (2010). COMPARISON OF NEURAL NETWORKS USED FOR PROCESSING AND CATEGORIZATION OF CZECH WRITTEN DOCUMENTS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 510-513. DOI: 10.5220/0003116205100513

in Bibtex Style

@conference{kdir10,
author={Pavel Mautner and Roman Mouček},
title={COMPARISON OF NEURAL NETWORKS USED FOR PROCESSING AND CATEGORIZATION OF CZECH WRITTEN DOCUMENTS},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={510-513},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003116205100513},
isbn={978-989-8425-28-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - COMPARISON OF NEURAL NETWORKS USED FOR PROCESSING AND CATEGORIZATION OF CZECH WRITTEN DOCUMENTS
SN - 978-989-8425-28-7
AU - Mautner P.
AU - Mouček R.
PY - 2010
SP - 510
EP - 513
DO - 10.5220/0003116205100513