Translating Quran verses result using indexed references

Mohd Yunus, Mohd Amin and Mohd Salleh, Mohd Najib and Lubis, Muharman and Omar, Nurul Aswa and Mustapha, Aida (2020) Translating Quran verses result using indexed references. Academia of Information Computing Research, 1 (1). pp. 10-21. ISSN 2716-6465

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Documents translations are still ambiguous when we translate them using by word, by phrase or by context technically separately and based on different readers’ understandings. Typically, the documents translation in different languages is found not well structured technically that leads to the misunderstanding amongst readers. Hence, there is a necessity for improving the Quran documents translation for providing the right sentences (ayats) in other languages as better as possible technically. The concept of source language and target languages is most importantly in designing the right algorithm as new approach for explaining the source of documents language in the form of the target of documents languages. In designing a new approach based on the said concept, the indexing technique is necessarily for retrieving the target translation from target language as called as multilingual information retrieval (MLIR). Thus, this paper proposes the Indexed References for retrieving the target-translated documents based on the structure index of each document (text file). Thus, Quran documents are translated easier based on unique structure index of each documents either indexing each Surah (Chapters) or indexing each Ayah (Verses) plus Surah as a unique reference. The documents translations retrieval based on Indexed Reference technique is more accurate at 99.99% comparing to the experimental separation of by word, by phrase and by concept translation technique. The proposed technique is useful for documents-to- documents translation retrieval in all languages of world.

Item Type: Article
Uncontrolled Keywords: Indexed references Numbers; MLIR
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Miss Afiqah Faiqah Mohd Hafiz
Date Deposited: 28 Feb 2022 06:39
Last Modified: 28 Feb 2022 06:39

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