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Research on the automatic construction of bilingual dictionaries has achieved impressive results. Bilingual dictionaries are usually constructed from parallel corpora, but since these corpora are available only for selected text domains and language pairs, the potential of other resources is being explored as well.In this article, we want to further pursue the idea of using Wikipedia as a corpus for bilingual terminology extraction. We propose a method that extracts term-translation pairs from different types of Wikipedia link information. After that, an SVM classifier trained on the features of manually labeled training data determines the correctness of unseen term-translation pairs.

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With the demand for bilingual dictionaries covering domain-specific terminology, research in the field of automatic dictionary extraction has become popular. However, the accuracy and coverage of dictionaries created based on bilingual text corpora are often not sufficient for domain-specific terms. Therefore, we present an approach for extracting bilingual dictionaries from the link structure of Wikipedia, a huge scale encyclopedia that contains a vast number of links between articles in different languages. Our methods analyze not only these interlanguage links but extract even more translations from redirect page and link text information. In an experiment which we have interpreted in detail, we proved that the combination of redirect page and link text information achieves much better results than the traditional approach of extracting bilingual terminology from parallel corpora.