title: Evaluating a pivot-based approach for bilingual lexicon extraction.
abstract: A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like English. In this paper, in order to show validity and usability of the pivot-based approach, we evaluate the approach in company with two different methods for estimating context vectors: one estimates them from two parallel corpora based on word association between source words (resp., target words) and pivot words and the other estimates them from two parallel corpora based on word alignment tools for statistical machine translation. Empirical results on two language pairs (e.g., Korean-Spanish and Korean-French) have shown that the pivot-based approach is very promising for resource-poor languages and this approach observes its validity and usability. Furthermore, for words with low frequency, our method is also well performed.
authors.affiliation: Department of Computer Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-gu, Busan 606-791, Republic of Korea.
authors.forename: Jae-Hoon
authors.initials: JH
authors.lastname: Kim
authors.affiliation: Department of Computer Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-gu, Busan 606-791, Republic of Korea.
authors.forename: Hong-Seok
authors.initials: HS
authors.lastname: Kwon
authors.affiliation: Department of Computer Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-gu, Busan 606-791, Republic of Korea.
authors.forename: Hyeong-Won
authors.initials: HW
authors.lastname: Seo
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D019303:Multilingualism; D009323:Natural Language Processing; D012660:Semantics; D014175:Translating; D014825:Vocabulary