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- W2104718911 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." @default.
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- W2104718911 date "2012-07-08" @default.
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- W2104718911 title "Learning to Find Translations and Transliterations on the Web" @default.
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