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Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach

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Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach

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Banerjee, S.; Kumar Naskar, S.; Rosso, P.; Bandyopadhyay, S. (2018). Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach. Journal of Intelligent & Fuzzy Systems. 34(5):2959-2969. https://doi.org/10.3233/JIFS-169481

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/120700

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Title: Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] Before the advent of the Internet era, code-mixing was mainly used in the spoken form. However, with the recent popular informal networking platforms such as Facebook, Twitter, Instagram, etc., in social media, ...[+]
Subjects: Question answering , Code-mixing , Cross-scripting , Question classification , Deep learning , Social media content
Copyrigths: Reserva de todos los derechos
Source:
Journal of Intelligent & Fuzzy Systems. (issn: 1064-1246 )
DOI: 10.3233/JIFS-169481
Publisher:
IOS Press
Publisher version: https://doi.org/10.3233/JIFS-169481
Thanks:
The work of the third author was partially supported by the SomEMBED TIN2015-71147-C2-1-P MINECO research project.
Type: Artículo

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