Single Term Concepts from English Translated Quran Using Statistical Methods
Ontology is essential for the success of knowledge based systems because it has the opportunity to share vocabulary, integrate knowledge easily and discover new instances or relations. However, the development of ontology via manual is time consuming and tedious task. Thus, ontology learning comes...
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my-unisza-ir.12832020-11-11T07:02:07Z http://eprints.unisza.edu.my/1283/ Single Term Concepts from English Translated Quran Using Statistical Methods Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar HA Statistics QA76 Computer software Ontology is essential for the success of knowledge based systems because it has the opportunity to share vocabulary, integrate knowledge easily and discover new instances or relations. However, the development of ontology via manual is time consuming and tedious task. Thus, ontology learning comes to play it roles. The ontology learning tries to extract ontological elements to support the ontology development. Concept extraction is one of the important tasks in ontology learning. The Hajj domain of Quranic study, concepts have not fully discovered. Hence, this paper tries to discover concepts by extracting the single terms from Qur’an translated version. It provides result on extracting the single terms as concepts by using statistical methods. Apart from that, it has been experiment for English Translated Quran by Hilali Khan. Result shows that the performance of using tf method as a statistical method is significant with the f-measure value is 0.509. Based on the tf, the comparisons have been made for other statistical methods such as tfidf, Avetf and Ridf. 2017 Conference or Workshop Item NonPeerReviewed text en http://eprints.unisza.edu.my/1283/1/FH03-FIK-18-12016.pdf Rohana, Ismail and Nurazzah, Abd Rahman and Zainab, Abu Bakar (2017) Single Term Concepts from English Translated Quran Using Statistical Methods. In: International Conference on Informatics, Computing and Applied Mathematics, 11 January 2017, UniSZA. |
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HA Statistics QA76 Computer software Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar Single Term Concepts from English Translated Quran Using Statistical Methods |
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Ontology is essential for the success of knowledge based systems because it has the opportunity to share vocabulary,
integrate knowledge easily and discover new instances or relations. However, the development of ontology via manual is
time consuming and tedious task. Thus, ontology learning comes to play it roles. The ontology learning tries to extract
ontological elements to support the ontology development. Concept extraction is one of the important tasks in ontology
learning. The Hajj domain of Quranic study, concepts have not fully discovered. Hence, this paper tries to discover concepts
by extracting the single terms from Qur’an translated version. It provides result on extracting the single terms as concepts by
using statistical methods. Apart from that, it has been experiment for English Translated Quran by Hilali Khan. Result shows
that the performance of using tf method as a statistical method is significant with the f-measure value is 0.509. Based on the
tf, the comparisons have been made for other statistical methods such as tfidf, Avetf and Ridf. |
format |
Conference or Workshop Item |
author |
Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar |
author_facet |
Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar |
author_sort |
Rohana, Ismail |
title |
Single Term Concepts from English Translated Quran Using Statistical Methods |
title_short |
Single Term Concepts from English Translated Quran Using Statistical Methods |
title_full |
Single Term Concepts from English Translated Quran Using Statistical Methods |
title_fullStr |
Single Term Concepts from English Translated Quran Using Statistical Methods |
title_full_unstemmed |
Single Term Concepts from English Translated Quran Using Statistical Methods |
title_sort |
single term concepts from english translated quran using statistical methods |
publishDate |
2017 |
url |
http://eprints.unisza.edu.my/1283/1/FH03-FIK-18-12016.pdf http://eprints.unisza.edu.my/1283/ |
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1683234999490314240 |
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