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Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction
Joint Authors
Kim, Jae-Hoon
Kwon, Hong-Seok
Seo, Hyeong-Won
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Kim, Jae-Hoon& Kwon, Hong-Seok& Seo, Hyeong-Won. 2015. Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057701
Modern Language Association (MLA)
Kim, Jae-Hoon…[et al.]. Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1057701
American Medical Association (AMA)
Kim, Jae-Hoon& Kwon, Hong-Seok& Seo, Hyeong-Won. Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057701
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057701