Omoush, Ashraf and Md Norwawi, Norita and Ismail, Roesnita and Abdul Wahid, Fauziah and Mazlan, Ahmad Akmaluddin (2017) Storage optimization for digital Quran using sparse matrix with hexadecimal representation. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur.

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Abstract

Digital Quran is a common application today in smart devices such as hand phones and tablet. The verses are usually presented using images of verses on written in an Arabic font.This raise issues related to storage when representing the whole Quran text.This study proposed a hexadecimal digital representation technique for words in Arabic using UTF-8 for character encoding which is backward compatible with ASCII code.This paper will explain three approaches used in representing the digital Quran.They are the hexadecimal representation for each Quranic words, sparse matrix in representing verses of Al-Quran and double offset indexing for transforming the sparse matrix to efficiently use the space. This representation proof more than 50% reduction in the memory space for storage thus will increase the searching speed.The storage of words being optimized through the use of one memory space for that particular word rather than one memory space for each Arabic character in the words .This technique helps optimized memory management for the whole digital Quran.Due to the smaller size, the digital Quran can be conveniently installed in the future as standard applications in mobile devices.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	eISSN 2289-7402 e-ISBN 978-967-0910-33-8 Organized by: School of Computing, Universiti Utara Malaysia Sintok.
Uncontrolled Keywords:	Digital Quran, Unicode, Mapping, Indexing, UTF-8
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	26 Jul 2017 08:18
Last Modified:	26 Jul 2017 08:18
URI:	https://repo.uum.edu.my/id/eprint/22820

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