Original title: Language-Independent Text Classifier Based On Recurrent Neural Networks
Authors: Myska, Vojtech
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: 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%.
Keywords: deep learning; recurrent neural networks; sentiment analysis
Host item entry: Proceedings of the 25st Conference STUDENT EEICT 2019, ISBN 978-80-214-5735-5

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/186773

Permalink: http://www.nusl.cz/ntk/nusl-414675


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers