Mining the Web for Domain-Specific Translations
Jian-Cheng Wu, Peter Wei-Huai Hsu, Chiung-Hui Tseng, Jason S. Chang
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.- Anthology ID:
- 2008.amta-papers.20
- Volume:
- Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
- Month:
- October 21-25
- Year:
- 2008
- Address:
- Waikiki, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 212–221
- Language:
- URL:
- https://aclanthology.org/2008.amta-papers.20
- DOI:
- Cite (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.
- Cite (Informal):
- Mining the Web for Domain-Specific Translations (Wu et al., AMTA 2008)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2008.amta-papers.20.pdf