Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction

Hadith is the second most important source used by all Muslims. However, semantic ambiguity in the hadith raises issues such as misinterpretation, misunderstanding, and misjudgement of the hadith’s content. How to tackle the semantic ambiguity will be focused on this research (RQ). The Zakat hadith...

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Main Author:	Ruziana, Mohamad Rasli
Format:	Thesis
Language:	eng eng
Published:	2022
Subjects:	BP Islam Bahaism Theosophy, etc BP174 The practice of Islam
Online Access:	https://etd.uum.edu.my/10196/1/s94645_01.pdf https://etd.uum.edu.my/10196/2/s94645_02.pdf
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id	my-uum-etd.10196
record_format	uketd_dc
spelling	my-uum-etd.101962023-01-08T00:44:41Z Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction 2022 Ruziana, Mohamad Rasli Kamaruddin, Siti Sakira Ahmad, Faudziah Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts & Sciences BP Islam. Bahaism. Theosophy, etc BP174 The practice of Islam Hadith is the second most important source used by all Muslims. However, semantic ambiguity in the hadith raises issues such as misinterpretation, misunderstanding, and misjudgement of the hadith’s content. How to tackle the semantic ambiguity will be focused on this research (RQ). The Zakat hadith data should be expressed semantically by changing the surface-level semantics to a deeper sense of the intended meaning. This can be achieved using an ontology model covering three main aspects (i.e., semantic relationship extraction, causal relationship representation, and suggestion extraction). This study aims to resolve the semantic ambiguity in hadith, particularly in the Zakat topic by proposing a semantic approach to resolve semantic ambiguity, representing causal relationships in the Zakat ontology model, proposing methods to extract suggestion polarity in hadith, and building the ontology model for Zakat topic. The selection of the Zakat topic is based on the survey findings that respondents still lack knowledge and understanding of the Zakat process. Four hadith book types (i.e., Sahih Bukhari, Sahih Muslim, Sunan Abu Dawud, and Sunan Ibn Majah) that was covering 334 concept words and 247 hadiths were analysed. The Zakat ontology modelling cover three phases which are Preliminary study, source selection and data collection, data pre-processing and analysis, and development and evaluation of ontology models. Domain experts in language, Zakat hadith, and ontology have evaluated the Zakat ontology and identified that 85% of Zakat concept was defined correctly. The Ontology Usability Scale was used to evaluate the final ontology model. An expert in ontology development evaluated the ontology that was developed in Protégé OWL, while 80 respondents evaluated the ontology concepts developed in PHP systems. The evaluation results show that the Zakat ontology has resolved the issue of ambiguity and misunderstanding of the Zakat process in the Zakat hadith. The Zakat ontology model also allows practitioners in Natural language processing (NLP), hadith, and ontology to extract Zakat hadith based on the representation of a reusable formal model, as well as causal relationships and the suggestion polarity of the Zakat hadith. 2022 Thesis https://etd.uum.edu.my/10196/ https://etd.uum.edu.my/10196/1/s94645_01.pdf text eng 2024-07-27 staffonly https://etd.uum.edu.my/10196/2/s94645_02.pdf text eng public other doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Kamaruddin, Siti Sakira Ahmad, Faudziah
topic	BP Islam Bahaism Theosophy, etc BP174 The practice of Islam
spellingShingle	BP Islam Bahaism Theosophy, etc BP174 The practice of Islam Ruziana, Mohamad Rasli Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
description	Hadith is the second most important source used by all Muslims. However, semantic ambiguity in the hadith raises issues such as misinterpretation, misunderstanding, and misjudgement of the hadith’s content. How to tackle the semantic ambiguity will be focused on this research (RQ). The Zakat hadith data should be expressed semantically by changing the surface-level semantics to a deeper sense of the intended meaning. This can be achieved using an ontology model covering three main aspects (i.e., semantic relationship extraction, causal relationship representation, and suggestion extraction). This study aims to resolve the semantic ambiguity in hadith, particularly in the Zakat topic by proposing a semantic approach to resolve semantic ambiguity, representing causal relationships in the Zakat ontology model, proposing methods to extract suggestion polarity in hadith, and building the ontology model for Zakat topic. The selection of the Zakat topic is based on the survey findings that respondents still lack knowledge and understanding of the Zakat process. Four hadith book types (i.e., Sahih Bukhari, Sahih Muslim, Sunan Abu Dawud, and Sunan Ibn Majah) that was covering 334 concept words and 247 hadiths were analysed. The Zakat ontology modelling cover three phases which are Preliminary study, source selection and data collection, data pre-processing and analysis, and development and evaluation of ontology models. Domain experts in language, Zakat hadith, and ontology have evaluated the Zakat ontology and identified that 85% of Zakat concept was defined correctly. The Ontology Usability Scale was used to evaluate the final ontology model. An expert in ontology development evaluated the ontology that was developed in Protégé OWL, while 80 respondents evaluated the ontology concepts developed in PHP systems. The evaluation results show that the Zakat ontology has resolved the issue of ambiguity and misunderstanding of the Zakat process in the Zakat hadith. The Zakat ontology model also allows practitioners in Natural language processing (NLP), hadith, and ontology to extract Zakat hadith based on the representation of a reusable formal model, as well as causal relationships and the suggestion polarity of the Zakat hadith.
format	Thesis
qualification_name	other
qualification_level	Doctorate
author	Ruziana, Mohamad Rasli
author_facet	Ruziana, Mohamad Rasli
author_sort	Ruziana, Mohamad Rasli
title	Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
title_short	Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
title_full	Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
title_fullStr	Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
title_full_unstemmed	Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
title_sort	ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2022
url	https://etd.uum.edu.my/10196/1/s94645_01.pdf https://etd.uum.edu.my/10196/2/s94645_02.pdf
_version_	1776103763564560384

Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction

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