Deep Neural Networks for Czech Multi-label Document Classification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952035" target="_blank" >RIV/49777513:23520/18:43952035 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-75487-1_36" target="_blank" >http://dx.doi.org/10.1007/978-3-319-75487-1_36</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-75487-1_36" target="_blank" >10.1007/978-3-319-75487-1_36</a>

Result language

angličtina

Original language name

Deep Neural Networks for Czech Multi-label Document Classification

Original language description

This paper is focused on automatic multi-label document classification of Czech text documents. The current approaches usually use some preprocessing which can have negative impact. Therefore, we would like to omit it and use deep neural networks that learn from simple features. This choice was motivated by their successful usage in many other machine learning fields. Two different networks are compared: the first one is a standard multi-layer perceptron, while the second one is a popular convolutional network. The experiments on a Czech newspaper corpus show that both networks significantly outperform baseline method which uses a rich set of features with maximum entropy classifier. We have also shown that convolutional network gives the best results.

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)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

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

Article name in the collection

Computational Linguistics and Intelligent Text Processing

ISBN

978-3-319-75486-4

ISSN

0302-9743

e-ISSN

neuvedeno

Number of pages

12

Pages from-to

460-471

Publisher name

Springer International Publishing AG,

Place of publication

Switzerland, Cham

Event location

Konya, Turkey

Event date

Apr 3, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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