Improving Machine Translation through Linked Data
Improving Machine Translation through Linked Data
About this item
Full title
Author / Creator
Publisher
Prague: De Gruyter Open
Journal title
Language
English
Formats
Publication information
Publisher
Prague: De Gruyter Open
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More information
Scope and Contents
Contents
With the ever increasing availability of linked multilingual lexical resources, there is a renewed interest in extending Natural Language Processing (NLP) applications so that they can make use of the vast set of lexical knowledge bases available in the Semantic Web. In the case of Machine Translation, MT systems can potentially benefit from such a...
Alternative Titles
Full title
Improving Machine Translation through Linked Data
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_proquest_journals_1913518421
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_1913518421
Other Identifiers
ISSN
1804-0462,0032-6585
E-ISSN
1804-0462
DOI
10.1515/pralin-2017-0033
