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Computational Intelligence and Neuroscience
Volume 2015, Article ID 434153, 13 pages
http://dx.doi.org/10.1155/2015/434153
Research Article

Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction

Department of Computer Engineering, Korea Maritime and Ocean University, 727 Taejong-ro, Yeongdo-gu, Busan 606-791, Republic of Korea

Received 29 December 2014; Revised 26 March 2015; Accepted 9 April 2015

Academic Editor: Francesco Camastra

Copyright © 2015 Jae-Hoon Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.