Combination of Neural Networks for Multi-label Document Classification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932538" target="_blank" >RIV/49777513:23520/17:43932538 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-59569-6_34" target="_blank" >http://dx.doi.org/10.1007/978-3-319-59569-6_34</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-59569-6_34" target="_blank" >10.1007/978-3-319-59569-6_34</a>

Result language

angličtina

Original language name

Combination of Neural Networks for Multi-label Document Classification

Original language description

This paper deals with multi-label classification of Czech documents using several combinations of neural networks. It is motivated by the assumption that different nets can keep some complementary information and that it should be useful to combine them. The main contribution of this paper consists in a comparison of several combination approaches to improve the results of the individual neural nets. We experimentally show that the results of all the combination approaches outperform the individual nets, however they are comparable.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Natural Language Processing and Information Systems. NLDB 2017

ISBN

978-3-319-59568-9

ISSN

0302-9743

e-ISSN

neuvedeno

Number of pages

5

Pages from-to

278-282

Publisher name

Springer

Place of publication

Cham

Event location

Liege, Belgium

Event date

Jun 21, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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