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Dimensionality reduction methods for machine translation quality estimation

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Dimensionality reduction methods for machine translation quality estimation

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González Rubio, J.; Navarro Cerdan, JR.; Casacuberta Nolla, F. (2013). Dimensionality reduction methods for machine translation quality estimation. Machine Translation. 27(3-4):281-301. doi:10.1007/s10590-013-9139-3

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/39000

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Title: Dimensionality reduction methods for machine translation quality estimation
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
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Abstract:
[EN] Quality estimation (QE) for machine translation is usually addressed as a regression problem where a learning model is used to predict a quality score from a (usually highly-redundant) set of features that represent ...[+]
Subjects: Machine translation , Quality estimation , Dimensionality reduction , Partial least squares regression
Copyrigths: Reserva de todos los derechos
Source:
Machine Translation. (issn: 0922-6567 )
DOI: 10.1007/s10590-013-9139-3
Publisher:
Springer Verlag (Germany)
Publisher version: http://link.springer.com/article/10.1007/s10590-013-9139-3
Project ID: info:eu-repo/grantAgreement/EC/FP7/287576
Description: The final publication is available at Springer via http://dx.doi.org/10.1007/s10590-013-9139-3
Thanks:
This work supported by the European Union Seventh Framework Program (FP7/2007-2013) under the CasMaCat project (grants agreement no. 287576), by Spanish MICINN under TIASA (TIN2009-14205-C04-02) project, and by the Generalitat ...[+]
Type: Artículo

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