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Author: Sung-Dong Kim

Affiliation: School of Computer Engineering, Hansung University, Seoul and Republic of Korea

Keyword(s): English-Korean Machine Translation, Comma Usage Analysis, Natural Language Processing, Rule-based Machine Translation.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Symbolic Systems

Abstract: Current English-Korean machine translation system cannot provide practical translation quality mainly due to the difficulties in long sentence parsing. Long sentences generally include commas, resulting in lots of different possible sentence structures. It is very difficult to accurately parse the long sentences that have commas. The roles of the commas in constructing sentences have to be identified and then the syntactic analysis should be performed according to the roles of the commas for accurate parsing of the long sentences. This paper presents the analysis results of the comma usages and the comma processing methods for each comma usage. And it also proposes the comma usage classification method using machine learning technique. In experiment, some improved translation results, by identifying comma usage and processing the commas, are also presented.

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Paper citation in several formats:
Kim, S. (2019). Comma Analysis and Processing for Improving Translation Quality of Long Sentences in Rule-based English-Korean Machine Translation. In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-350-6; ISSN 2184-433X, SciTePress, pages 474-479. DOI: 10.5220/0007310604740479

@conference{icaart19,
author={Sung{-}Dong Kim.},
title={Comma Analysis and Processing for Improving Translation Quality of Long Sentences in Rule-based English-Korean Machine Translation},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2019},
pages={474-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007310604740479},
isbn={978-989-758-350-6},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Comma Analysis and Processing for Improving Translation Quality of Long Sentences in Rule-based English-Korean Machine Translation
SN - 978-989-758-350-6
IS - 2184-433X
AU - Kim, S.
PY - 2019
SP - 474
EP - 479
DO - 10.5220/0007310604740479
PB - SciTePress

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