Automatic Translation of Multi-word Labels
Grzegorz M. Protaziuk
,
Marcin Kaczyński
,
Robert Bembenik
Abstract
Application of semantic resources often requires linking phrases expressed in a natural language to formally defined notions. In case of ontologies lexical layers may be used for that purpose. In the paper we propose an automatic machine translation method for translating multi-word labels from lexical layers of domain ontologies. In the method we take advantage of Wikipedia and dictionaries services available on the Internet in order to provide translations of thematic texts from a given area of interest. Experimental evaluation shows usefulness of the proposed method in translating specialized thematic dictionaries.Author |
Grzegorz M. Protaziuk (FEIT / IN)
Grzegorz M. Protaziuk,,
- The Institute of Computer Science
,
Marcin Kaczyński (FEIT / IN)
Marcin Kaczyński,,
- The Institute of Computer Science
,
Robert Bembenik (FEIT / IN)
Robert Bembenik,,
- The Institute of Computer Science
|
Pages | 99-109 |
Publication size in sheets | 0.5 |
Book |
Ryżko Dominik Paweł, Gawrysiak Piotr, Kryszkiewicz Marzena, Rybiński Henryk (eds.): Machine Intelligence and Big Data in Industry, Studies in Big Data, vol. 19, 2016, Springer International Publishing Switzerland, ISBN 978-3-319-30314-7, [978-3-319-30315-4], 236 p., DOI:10.1007/978-3-319-30315-4
|
Keywords in English | Domain label translation – Automatic translation – Wikipedia application |
DOI | DOI:10.1007/978-3-319-30315-4_9 |
URL |
http://link.springer.com/chapter/10.1007/978-3-319-30315-4_9 |
Project | Development of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk,
, Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI
Działalność statutowa
|
Language | en angielski |
File | |
Score (nominal) | 15 |
Score source | conferenceIndex |
Score | Ministerial score = 15.0, 17-10-2020, BookChapterSeriesAndMatConfByIndicator Ministerial score (2013-2016) = 15.0, 17-10-2020, BookChapterSeriesAndMatConfByIndicator |
Publication indicators |
WoS Citations = 0;
GS Citations = 1.0 |
Citation count* | 1 (2021-01-12) |
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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