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篇名
Learning to Find Translations and Transliterations on the Web based on Conditional Random Fields
作者 Joseph Z. Chang (Joseph Z. Chang)Jason S. Chang (Jason S. Chang)Jyh-Shing Roger Jang (Jyh-Shing Roger Jang)
中文摘要
In recent years, state-of-the-art cross-linguistic systems have been based on parallel corpora. Nevertheless, it is difficult at times to find translations of a certain technical term or named entity even with a very large parallel corpora. In this paper, we present a new method for learning to find translations on the Web for a given term. In our approach, we use a small set of terms and translations to obtain mixed-code snippets returned by a search engine. We then automatically annotate the data with translation tags, automatically generate features to augment the tagged data, and automatically train a conditional random fields model for identifying translations. At runtime, we obtain mixed-code webpages containing the given term and run the model to extract translations as output. Preliminary experiments and evaluation results show our method cleanly combines various features, resulting in a system that outperforms previous works.
起訖頁 19-45
關鍵詞 Machine TranslationCross-lingual Information ExtractionWikipediaConditional Random Fields.
刊名 中文計算語言學期刊  
期數 201303 (18:1期)
出版單位 中華民國計算語言學學會
該期刊-上一篇 Lexical Coverage in Taiwan Mandarin Conversation
該期刊-下一篇 Machine Translation Approaches and Survey for Indian Languages
 

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