Bilingual Contexts From Comparable Corpora To Mine For Translations Of Collocations

COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, (CICLING 2016), PT II(2018)

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摘要
Due to the limited availability of parallel data in many languages, we propose a methodology that benefits from comparable corpora to find translation equivalents for collocations (as a specific type of difficult-to-translate multi-word expressions). Finding translations is known to be more difficult for collocations than for words. We propose a method based on bilingual context extraction and build a word (distributional) representation model drawing on these bilingual contexts (bilingual English-Spanish contexts in our case). We show that the bilingual context construction is effective for the task of translation equivalent learning and that our method outperforms a simplified distributional similarity baseline in finding translation equivalents.
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关键词
Collocations, Word vector representation, Distributional similarity, Comparable corpora
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