Noun Sense Disambiguation using Co-Occurrence Relation in Machine Translation

Choe, Changil, and Kim, Hyonil. "Noun Sense Disambiguation using Co-Occurrence Relation in Machine Translation." Serdica Journal of Computing 6.4 (2012): 401-408. <http://eudml.org/doc/250963>.

@article{Choe2012,
abstract = {Word Sense Disambiguation, the process of identifying the meaning of a word in a sentence when the word has multiple meanings, is a critical problem of machine translation. It is generally very difficult to select the correct meaning of a word in a sentence, especially when the syntactical difference between the source and target language is big, e.g., English-Korean machine translation. To achieve a high level of accuracy of noun sense selection in machine translation, we introduced a statistical method based on co-occurrence relation of words in sentences and applied it to the English-Korean machine translator RyongNamSan. ACM Computing Classification System (1998): I.2.7.},
author = {Choe, Changil, Kim, Hyonil},
journal = {Serdica Journal of Computing},
keywords = {Machine Translation; Statistical Method; Word Sense Disambiguation; Co-occurrence Relation; Bilingual Corpus},
language = {eng},
number = {4},
pages = {401-408},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {Noun Sense Disambiguation using Co-Occurrence Relation in Machine Translation},
url = {http://eudml.org/doc/250963},
volume = {6},
year = {2012},
}

TY - JOUR
AU - Choe, Changil
AU - Kim, Hyonil
TI - Noun Sense Disambiguation using Co-Occurrence Relation in Machine Translation
JO - Serdica Journal of Computing
PY - 2012
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 6
IS - 4
SP - 401
EP - 408
AB - Word Sense Disambiguation, the process of identifying the meaning of a word in a sentence when the word has multiple meanings, is a critical problem of machine translation. It is generally very difficult to select the correct meaning of a word in a sentence, especially when the syntactical difference between the source and target language is big, e.g., English-Korean machine translation. To achieve a high level of accuracy of noun sense selection in machine translation, we introduced a statistical method based on co-occurrence relation of words in sentences and applied it to the English-Korean machine translator RyongNamSan. ACM Computing Classification System (1998): I.2.7.
LA - eng
KW - Machine Translation; Statistical Method; Word Sense Disambiguation; Co-occurrence Relation; Bilingual Corpus
UR - http://eudml.org/doc/250963
ER -