Two-Level Neural Network for Multi-label Document Classification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932624" target="_blank" >RIV/49777513:23520/17:43932624 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-68612-7_42" target="_blank" >http://dx.doi.org/10.1007/978-3-319-68612-7_42</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-68612-7_42" target="_blank" >10.1007/978-3-319-68612-7_42</a>

Result language

angličtina

Original language name

Two-Level Neural Network for Multi-label Document Classification

Original language description

This paper deals with multi-label document classification using neural networks. We propose a novel neural network which is composed of two sub-nets: the first one estimates the scores for all classes, while the second one determines the number of classes assigned to the document. The proposed approach is evaluated on Czech and English standard corpora. The experimental results show that the proposed method is competitive with state of the art on both languages.

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

Artificial Neural Networks and Machine Learning – ICANN 2017

ISBN

978-3-319-68611-0

ISSN

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e-ISSN

neuvedeno

Number of pages

8

Pages from-to

368-375

Publisher name

Springer

Place of publication

Cham

Event location

Alghero, Italy

Event date

Sep 11, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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