@inproceedings{d51da007e35749d1a52fe4a2818fa36c,
title = "Target word selection as proximity in semantic space",
abstract = "Lexical selection is a significant problem for wide-coverage machine translation: depending on the context, a given source language word can often be translated into different target language words. In this paper I propose a method for target word selection that assumes the appropriate translation is more similar to the translated context than are the alternatives. Similarity of a word to a context is estimated using a proximity measure in corpus-derived {"}semantic space{"}. The method is evaluated using an English-Spanish parallel corpus of colloquial dialogue.",
author = "Scott McDonald",
year = "1998",
month = aug,
day = "10",
doi = "10.3115/980691.980818",
language = "English",
volume = "2",
series = "Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "1496--1498",
booktitle = "Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics (ACL '98/COLING '98)",
note = "36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, ACL '98/COLING '98 ; Conference date: 10-08-1998 Through 14-08-1998",
}