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

Pavel Mautner, Roman Mouček

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.

References

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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