Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop
Document classification retrieval is a method of selecting the right document that contains useful information. One of the data corpuses that can be stored in the document is Al-Quran Malay translation collection. Al-Quran is a holy book and can be extremely important document to Muslims. It is used...
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2014
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Online Access: | https://ir.uitm.edu.my/id/eprint/87145/1/87145.pdf |
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my-uitm-ir.871452024-01-30T02:15:25Z Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop 2014 Yusop, Yuhaini Document classification retrieval is a method of selecting the right document that contains useful information. One of the data corpuses that can be stored in the document is Al-Quran Malay translation collection. Al-Quran is a holy book and can be extremely important document to Muslims. It is used as a guidance to lead a righteous life. Most people read the Al-Quran along with its translation to understand the content or the meaning of the verses in each of the Surah (chapters). Each chapter describes information that can be referred to by Muslims with the help of the translation. However, it is not an easy task to search for information in the Malay translated Al-Quran since it contains many pages. Most of people find it hard to search the phrases manually in the Al-Quran, and it require a lot time consuming. Moreover, most of the searches are not related to what the user want. Therefore, the objective of this project is to develop Malay search query prototype for the Malay translated Al-Quran document where the user can search the information based on topic. 2014 Thesis https://ir.uitm.edu.my/id/eprint/87145/ https://ir.uitm.edu.my/id/eprint/87145/1/87145.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Mohammad, Norasiah |
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Universiti Teknologi MARA |
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UiTM Institutional Repository |
language |
English |
advisor |
Mohammad, Norasiah |
description |
Document classification retrieval is a method of selecting the right document that contains useful information. One of the data corpuses that can be stored in the document is Al-Quran Malay translation collection. Al-Quran is a holy book and can be extremely important document to Muslims. It is used as a guidance to lead a righteous life. Most people read the Al-Quran along with its translation to understand the content or the meaning of the verses in each of the Surah (chapters). Each chapter describes information that can be referred to by Muslims with the help of the translation. However, it is not an easy task to search for information in the Malay translated Al-Quran since it contains many pages. Most of people find it hard to search the phrases manually in the Al-Quran, and it require a lot time consuming. Moreover, most of the searches are not related to what the user want. Therefore, the objective of this project is to develop Malay search query prototype for the Malay translated Al-Quran document where the user can search the information based on topic. |
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Thesis |
qualification_level |
Bachelor degree |
author |
Yusop, Yuhaini |
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Yusop, Yuhaini Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
author_facet |
Yusop, Yuhaini |
author_sort |
Yusop, Yuhaini |
title |
Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
title_short |
Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
title_full |
Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
title_fullStr |
Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
title_full_unstemmed |
Topic based search for Malay translated Al-Quran documents / Yuhaini Yusop |
title_sort |
topic based search for malay translated al-quran documents / yuhaini yusop |
granting_institution |
Universiti Teknologi MARA (UiTM) |
granting_department |
Faculty of Computer and Mathematical Sciences |
publishDate |
2014 |
url |
https://ir.uitm.edu.my/id/eprint/87145/1/87145.pdf |
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1794192113961795584 |