TermMine is an information extraction system that can automatically mine translation pairs of terms from the web. We used a small set of terms and translations to gather mixed-code text from the web to train a CRF model that can identify translation pairs at run-time.

Abstract

In this paper, we present a new method for learning to finding translations and transliterations on the Web for a given term. The approach involves using a small set of terms and translations to obtain mixed-code snippets from a search engine, and automatically annotating the snippets with tags and features for training a conditional random field model. At run-time, the model is used to extracting translation candidates for a given term. Preliminary experiments and evaluation show our method cleanly combining various features, resulting in a system that outperforms previous work.

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Citation

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Joseph Z. Chang, Jason S. Chang, and Jyh-Shing Roger Jang. 2012.
Learning to find translations and transliterations on the web.
In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics.
Association for Computational Linguistics, Stroudsburg, PA, USA, 130-134.

Bibtex

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@inproceedings{Chang:2012:LFT:2390665.2390698,
 author = {Chang, Joseph Z. and Chang, Jason S. and Jang, Jyh-Shing Roger},
 title = {Learning to Find Translations and Transliterations on the Web},
 booktitle = {Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics},
 series = {ACL '12},
 year = {2012},
 location = {Jeju Island, Korea},
 pages = {130--134},
 numpages = {5},
 url = {http://dl.acm.org/citation.cfm?id=2390665.2390698},
 acmid = {2390698},
 publisher = {Association for Computational Linguistics},
 address = {Stroudsburg, PA, USA},
}