A Pattern for Concept Identification from English Translated Quran
Ontology development is time consuming and tedious task. The task can be minimized by automatic or semi-automatic ontology development. This minimizing task is a field of ontology learning. Ontology learning will be able to extract ontological elements to form ontology. Concept identifying is on...
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2017
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my-unisza-ir.13002020-11-11T08:07:58Z http://eprints.unisza.edu.my/1300/ A Pattern for Concept Identification from English Translated Quran Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar QA75 Electronic computers. Computer science Ontology development is time consuming and tedious task. The task can be minimized by automatic or semi-automatic ontology development. This minimizing task is a field of ontology learning. Ontology learning will be able to extract ontological elements to form ontology. Concept identifying is one of the important activities in ontology learning. Various methods can be used to find concepts. Thus, this experiment used the n-grams and JAPE pattern in identifying concepts. As the term Allah occurs very frequent in English translated Quran, this experiment considers the word surrounding the term Allah to find other related concepts. It is important because the occurrences produced the term Allah as a concept in ontology but at the same time ignore other related terms to term Allah. The strength connection between words surrounding term Allah has been analysed. Results show the significant terms related to term Allah can be extracted. Later, the term can be used as concepts in ontology. 2017 Conference or Workshop Item NonPeerReviewed text en http://eprints.unisza.edu.my/1300/1/FH03-FIK-17-11967.pdf text en http://eprints.unisza.edu.my/1300/2/FH03-FIK-17-11966.pdf Rohana, Ismail and Nurazzah, Abd Rahman and Zainab, Abu Bakar (2017) A Pattern for Concept Identification from English Translated Quran. In: 8th International Conference on Mechanical and Manufacturing Engineering 2017 (ICME’17), 22-23 July 2017, Langkawi, Malaysia. |
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QA75 Electronic computers. Computer science Rohana, Ismail Nurazzah, Abd Rahman Zainab, Abu Bakar A Pattern for Concept Identification from English Translated Quran |
description |
Ontology development is time consuming and tedious task. The
task can be minimized by automatic or semi-automatic ontology
development. This minimizing task is a field of ontology learning.
Ontology learning will be able to extract ontological elements to form
ontology. Concept identifying is one of the important activities in ontology
learning. Various methods can be used to find concepts. Thus, this
experiment used the n-grams and JAPE pattern in identifying concepts. As
the term Allah occurs very frequent in English translated Quran, this
experiment considers the word surrounding the term Allah to find other
related concepts. It is important because the occurrences produced the term
Allah as a concept in ontology but at the same time ignore other related
terms to term Allah. The strength connection between words surrounding
term Allah has been analysed. Results show the significant terms related to
term Allah can be extracted. Later, the term can be used as concepts in
ontology. |
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 |
A Pattern for Concept Identification from English Translated Quran |
title_short |
A Pattern for Concept Identification from English Translated Quran |
title_full |
A Pattern for Concept Identification from English Translated Quran |
title_fullStr |
A Pattern for Concept Identification from English Translated Quran |
title_full_unstemmed |
A Pattern for Concept Identification from English Translated Quran |
title_sort |
pattern for concept identification from english translated quran |
publishDate |
2017 |
url |
http://eprints.unisza.edu.my/1300/1/FH03-FIK-17-11967.pdf http://eprints.unisza.edu.my/1300/2/FH03-FIK-17-11966.pdf http://eprints.unisza.edu.my/1300/ |
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