Detail publikačního výsledku

Language-Independent Text Classifier Base on Recurrent Neural Networks

MYŠKA, V.

Originální název

Language-Independent Text Classifier Base on Recurrent Neural Networks

Anglický název

Language-Independent Text Classifier Base on Recurrent Neural Networks

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper deals with a proposal of language independent text classifiers based on recurrent neural networks. They work at a character level thus they do not require any text preprocessing. The classifiers have been trained and evaluated on a multilingual data set that is privately collected from film review databases. It contains Czech (Slovak), English, German and Spanish language subset. The resulting accuracy of the proposed language independent classifiers base on the recurrent neural networks in polarity sentiment analysis task is 78.55%.

Anglický abstrakt

This paper deals with a proposal of language independent text classifiers based on recurrent neural networks. They work at a character level thus they do not require any text preprocessing. The classifiers have been trained and evaluated on a multilingual data set that is privately collected from film review databases. It contains Czech (Slovak), English, German and Spanish language subset. The resulting accuracy of the proposed language independent classifiers base on the recurrent neural networks in polarity sentiment analysis task is 78.55%.

Klíčová slova

sentiment analysis;recurrent neural networks;deep learning

Klíčová slova v angličtině

sentiment analysis;recurrent neural networks;deep learning

Autoři

MYŠKA, V.

Rok RIV

2020

Vydáno

25.04.2019

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo

Brno

ISBN

978-80-214-5735-5

Kniha

Proceedings of the 25th Conference STUDENT EEICT 2019

Strany od

754

Strany do

758

Strany počet

5

BibTex

@inproceedings{BUT157417,
  author="Vojtěch {Myška}",
  title="Language-Independent Text Classifier Base on Recurrent Neural Networks",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  year="2019",
  pages="754--758",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5735-5"
}