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Linguistically independent sentiment analysis using convolutional-recurrent neural networks model

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132720" target="_blank" >RIV/00216305:26220/19:PU132720 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/TSP.2019.8768887" target="_blank" >http://dx.doi.org/10.1109/TSP.2019.8768887</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TSP.2019.8768887" target="_blank" >10.1109/TSP.2019.8768887</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Linguistically independent sentiment analysis using convolutional-recurrent neural networks model

  • Original language description

    Text classification is a process which analyses text and assigns one or more classes to it based on its content. This paper introduces a linguistically independent text classifier based on convolutional–recurrent neural networks. The classifier works at character level instead of some higher structures such as words, sentences, etc. To evaluate the accuracy of the proposed methodology, the Yelp data set and other multilingual data set obtained from film review databases containing Czech, German and Spanish languages were used. The resulting accuracy on the Yelp data set is 93,64 %. We also proved that the proposed model can work for various languages.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2019 42nd International Conference on Telecommunications and Signal Processing (TSP)

  • ISBN

    978-1-7281-1864-2

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    212-215

  • Publisher name

    IEEE

  • Place of publication

    Budapest, Hungary

  • Event location

    Budapest, Hungary

  • Event date

    Jul 1, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000493442800046