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Automatic Acquisition of Parallel Corpora from Websites with Dynamic Content
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Automatic Acquisition of Parallel Corpora from Websites with Dynamic Content
Parallel corpora are indispensable resources for a variety of multilingual natural language processing tasks. This paper presents a technique for fully automatic construction of constantly growing parallel corpora. We propose a simple and effective dictionary-based algorithm to extract parallel document pairs from a large collection of articles retrieved from the Internet, potentially containing manually translated texts. This algorithm was implemented and tested on Hebrew-English parallel texts. With properly selected thresholds, precision of 100% can be obtained.
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