Analogy-based machine translation using secability

Tatsuya Kimura, Jin Matsuoka, Yusuke Nishikawa, Yves Lepage

研究成果: Conference contribution

抄録

The problem of reordering remains the main problem in machine translation. Computing structures of sentences and the alignment of substructures is a way that has been proposed to solve this problem. We use secability to compute structures and show its effectiveness in an example-based machine translation.

本文言語English
ホスト出版物のタイトルProceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
出版社IEEE Computer Society
ページ297-298
ページ数2
ISBN(印刷版)9781479930098
DOI
出版ステータスPublished - 2014
イベント2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 - Las Vegas, NV, United States
継続期間: 2014 3 102014 3 13

出版物シリーズ

名前Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
2

Conference

Conference2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
CountryUnited States
CityLas Vegas, NV
Period14/3/1014/3/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

引用スタイル