Detail publikace
Neural Network for Text Associations
ZBOŘIL, F.
Originální název
Neural Network for Text Associations
Anglický název
Neural Network for Text Associations
Jazyk
en
Originální abstrakt
The paper proposes a new neural network based on the principle of the Restricted Coulomb Energy (RCE) classifier. The network has three layers of neurons and it works as a heteroassociative memory. The short principles of the proposed neural network - topology, learning and retrieving - are described in the paper. Experiments with text lines associations that have been done with this neural network and with the Bidirectional Associative Memory (BAM) and a comparison of these results are described in the paper, too.
Anglický abstrakt
The paper proposes a new neural network based on the principle of the Restricted Coulomb Energy (RCE) classifier. The network has three layers of neurons and it works as a heteroassociative memory. The short principles of the proposed neural network - topology, learning and retrieving - are described in the paper. Experiments with text lines associations that have been done with this neural network and with the Bidirectional Associative Memory (BAM) and a comparison of these results are described in the paper, too.
Dokumenty
BibTex
@inproceedings{BUT5418,
author="František {Zbořil}",
title="Neural Network for Text Associations",
annote="The paper proposes a new neural network based on the principle of the Restricted Coulomb Energy (RCE) classifier. The network has three layers of neurons and it works as a heteroassociative memory. The short principles of the proposed neural network - topology, learning and retrieving - are described in the paper. Experiments with text lines associations that have been done with this neural network and with the Bidirectional Associative Memory (BAM) and a comparison of these results are described in the paper, too.",
booktitle="Proceedings of XXIInd International Colloquium ASIS 2000",
chapter="5418",
year="2000",
month="january",
pages="145--150",
type="conference paper"
}