Language-Independent Text Classifier Based On Recurrent Neural Networks
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Date
2019
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Mark
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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%.
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Proceedings of the 25st Conference STUDENT EEICT 2019. s. 754-758. ISBN 978-80-214-5735-5
http://www.feec.vutbr.cz/EEICT/
http://www.feec.vutbr.cz/EEICT/
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Peer-reviewed
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en
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© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií