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BITRA. BIBLIOGRAFÍA DE INTERPRETACIÓN Y TRADUCCIÓN

 
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Tema:   Interferencia. Normalización.
Autor:   Ilisei, Iustina
Año:   2013
Título:   A Machine Learning Approach to the Identification of Translational Language: An Inquiry Into Translationese Learning Models
Lugar:   Wolverhampton
http://clg.wlv.ac.uk/papers/ilisei-thesis.pdf
Editorial/Revista:   University of Wolverhampton
Páginas:   317
Idioma:   Inglés.
Tipo:   Tesis.
Disponibilidad:   Acceso abierto.
Índice:   1, Related Research; 2. Resources Required; 3. Investigation of Translational Language from A Machine Learning Perspective.
Resumen:   In the field of Descriptive Translation Studies, translationese refers to the specific traits that characterise the language used in translations. [..] While the main focus is on analysing translationese, this thesis investigates two related sub-hypotheses: simplification and explicitation.
[..] The framework is modelled as a categorisation task, the learning techniques having the major goal to automatically learn to distinguish between translated and non-translated texts. The second and third major goals of this research are the retrieval of the recurring patterns that are revealed in the process of solving the task of categorisation, as well as the ranking of the most influential characteristics used to accomplish the learning task. [..]
The present research is situated at the confluence of three areas, more precisely: Descriptive Translation Studies, Machine Learning and Natural Language Processing, justifying the need to combine these fields for the investigation of translationese and translational hypotheses. [Source: Author]
Agradecimientos:   Record supplied by Departament de Traducció i Interpretació i Estudis de l'Àsia Oriental (Universitat Autònoma de Barcelona).
 
 
2001-2021 Universidad de Alicante DOI: 10.14198/bitra
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