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Understanding Knowledge Representation Concepts in Machine Translation: A Review

by Goonatilleke, B. Hettige, Bandara
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 58
Year of Publication: 2024
Authors: Goonatilleke, B. Hettige, Bandara
10.5120/ijca2024924343

Goonatilleke, B. Hettige, Bandara . Understanding Knowledge Representation Concepts in Machine Translation: A Review. International Journal of Computer Applications. 186, 58 ( Dec 2024), 35-44. DOI=10.5120/ijca2024924343

@article{ 10.5120/ijca2024924343,
author = { Goonatilleke, B. Hettige, Bandara },
title = { Understanding Knowledge Representation Concepts in Machine Translation: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2024 },
volume = { 186 },
number = { 58 },
month = { Dec },
year = { 2024 },
issn = { 0975-8887 },
pages = { 35-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number58/understanding-knowledge-representation-concepts-in-machine-translation-a-review/ },
doi = { 10.5120/ijca2024924343 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-12-27T02:46:14.186014+05:30
%A Goonatilleke
%A B. Hettige
%A Bandara
%T Understanding Knowledge Representation Concepts in Machine Translation: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 58
%P 35-44
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Machine Translation is one of the core fields in Natural Language Processing and sub-branches in Artificial Intelligence, refers to a software that translates text or voice from one natural language into another natural language without human intervention. The major problem related to machine translation system is separating the translation algorithm from the grammatical rules due to the language complexity. As one of the solutions, the concept named knowledge representation can be used to address this problem. The aim of this paper is to deeply study the machine translation along with knowledge representation concept to understand the relationship between them that can be used to design accurate, well-performed machine translation systems. Therefore, the paper has focused on some interesting directions such as tasks of NLP, the process of machine translation, topology of latest machine translation approaches with their architectures and knowledge representation techniques. Moreover, the paper has reviewed twenty famous machine translations systems available in the world and captured their respective machine translation approach and knowledge representation technique. As the result of this study, it has been identified that most modern machine translation systems have used the concepts of machine learning due to some reasons such as data-driven learning, contextual understanding, scalability, continuous improvement and etc. Finally, the paper presented future directions of machine translation along with knowledge representation.

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Index Terms

Computer Science
Information Sciences
Artificial Intelligence
Natural Language Processing

Keywords

Machine Translation Knowledge Representation

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