Translating Quran Verses Result using Indexed References
Abstract
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.