@inproceedings{075586f20d31424e8ed39fec0af02bd1,
title = "Predicate-argument reordering based on learning to rank for english-korean machine translation",
abstract = "In this paper, we propose a method of learning predicateargument structure reordering, and present its effect on machine translation. The method takes two steps; first, it extracts generalized predicate-argument structure reordering rules using a source sentence parse tree from a parallel corpus. Second, it trains a model based on learning to rank framework to select the most relevant reordering rule based on source language context features. The learned model is used to restructure a source sentence in order to have similar word order with a target sentence. In our experiments on English-to-Korean machine translation, the proposed method achieves significant improvements in BLEU score, from 19.68 to 21.84.",
keywords = "Learning to rank, Machine translation, Predicate-argument, Preprocessing, Reordering",
author = "Lee, {Joo Young} and Gumwon Hong and Rim, {Hae Chang} and Song, {Young In} and Hwang, {Young Sook}",
year = "2011",
doi = "10.1145/1968613.1968616",
language = "English",
isbn = "9781450305716",
series = "Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011",
booktitle = "Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011",
note = "5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011 ; Conference date: 21-02-2011 Through 23-02-2011",
}