@inproceedings{wu-etal-2008-mining,
title = "Mining the Web for Domain-Specific Translations",
author = "Wu, Jian-Cheng and
Wei-Huai Hsu, Peter and
Tseng, Chiung-Hui and
Chang, Jason S.",
booktitle = "Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers",
month = oct # " 21-25",
year = "2008",
address = "Waikiki, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2008.amta-papers.20",
pages = "212--221",
abstract = "We introduce a method for learning to find domain-specific translations for a given term on the Web. In our approach, the source term is transformed into an expanded query aimed at maximizing the probability of retrieving translations from a very large collection of mixed-code documents. The method involves automatically generating sets of target-language words from training data in specific domains, automatically selecting target words for effectiveness in retrieving documents containing the sought-after translations. At run time, the given term is transformed into an expanded query and submitted to a search engine, and ranked translations are extracted from the document snippets returned by the search engine. We present a prototype, TermMine, which applies the method to a Web search engine. Evaluations over a set of domains and terms show that TermMine outperforms state-of-the-art machine translation systems.",
}
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<abstract>We introduce a method for learning to find domain-specific translations for a given term on the Web. In our approach, the source term is transformed into an expanded query aimed at maximizing the probability of retrieving translations from a very large collection of mixed-code documents. The method involves automatically generating sets of target-language words from training data in specific domains, automatically selecting target words for effectiveness in retrieving documents containing the sought-after translations. At run time, the given term is transformed into an expanded query and submitted to a search engine, and ranked translations are extracted from the document snippets returned by the search engine. We present a prototype, TermMine, which applies the method to a Web search engine. Evaluations over a set of domains and terms show that TermMine outperforms state-of-the-art machine translation systems.</abstract>
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%0 Conference Proceedings
%T Mining the Web for Domain-Specific Translations
%A Wu, Jian-Cheng
%A Wei-Huai Hsu, Peter
%A Tseng, Chiung-Hui
%A Chang, Jason S.
%S Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2008
%8 oct 21 25
%I Association for Machine Translation in the Americas
%C Waikiki, USA
%F wu-etal-2008-mining
%X We introduce a method for learning to find domain-specific translations for a given term on the Web. In our approach, the source term is transformed into an expanded query aimed at maximizing the probability of retrieving translations from a very large collection of mixed-code documents. The method involves automatically generating sets of target-language words from training data in specific domains, automatically selecting target words for effectiveness in retrieving documents containing the sought-after translations. At run time, the given term is transformed into an expanded query and submitted to a search engine, and ranked translations are extracted from the document snippets returned by the search engine. We present a prototype, TermMine, which applies the method to a Web search engine. Evaluations over a set of domains and terms show that TermMine outperforms state-of-the-art machine translation systems.
%U https://aclanthology.org/2008.amta-papers.20
%P 212-221
Markdown (Informal)
[Mining the Web for Domain-Specific Translations](https://aclanthology.org/2008.amta-papers.20) (Wu et al., AMTA 2008)
ACL
- Jian-Cheng Wu, Peter Wei-Huai Hsu, Chiung-Hui Tseng, and Jason S. Chang. 2008. Mining the Web for Domain-Specific Translations. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers, pages 212–221, Waikiki, USA. Association for Machine Translation in the Americas.