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http://cris.unibe.edu.do/handle/123456789/320| Title: | Improving a Japanese-Spanish machine translation system using Wikipedia medical articles | Autores: | Ramírez Vidal, Jessica C. Matsumoto, Y. Muñoz N., Darwin C. |
Researchers (UNIBE): | Ramírez Vidal, Jessica C. Muñoz N., Darwin C. |
Affiliations: | Facultad de Ciencias Básicas y Tecnológicas Facultad de Ciencias Básicas y Tecnológicas |
Research area: | Tecnología | Keywords: | Comparable Corpora; Dictionary; Ontology; Machine Translation | Issue Date: | 2015 | Publisher: | Academy & Industry Research Collaboration Center (AIRCC) | Source: | En: D. Wyld y J. Zizka (Eds.) Computer Science & Information Technology. Fifth International conference on Computer Science and Information Technology (CCSIT - 2015), pp. 111–116. | Project: | Sistema de traducción automática japonés-español usando inglés como lengua intermedia | Related Publication(s): | Computer Science & Information Technology. Fifth International Conference on Computer Science and Information Technology (CCSIT - 2015) | Start page: | 111 | End page: | 116 | Conference: | Fifth International Conference on Computer Science and Information Technology (CCSIT - 2015). Sydney, Australia, February 21-22, 2015 | Abstract: | The quality, length and coverage of a parallel corpus are fundamental features in the performance of a Statistical Machine Translation System (SMT). For some pair of languages there is a considerable lack of resources suitable for Natural Language Processing tasks. This paper introduces a technique for extracting medical information from the Wikipedia page. Using a medical ontological dictionary and then we evaluate on a Japanese-Spanish SMT system. The study shows an increment in the BLEU score. |
URI: | http://cris.unibe.edu.do/handle/123456789/320 | DOI: | 10.5121/csit.2015.50411 |
| Appears in Collections: | Publicaciones de la Facultad de Ciencias Básicas y Tecnológicas |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| csit53511.pdf | Full text [open access] | 534.17 kB | Adobe PDF | View/Open |
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