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...

Full description

Saved in:
Bibliographic Details
Main Author: Ruziana, Mohamad Rasli
Format: Thesis
Language:en
Published: 2022
Subjects:
Online Access:https://etd.uum.edu.my/10196/1/s94645_01.pdf
https://etd.uum.edu.my/10196/
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1842851220734083072
author Ruziana, Mohamad Rasli
author_facet Ruziana, Mohamad Rasli
author_sort Ruziana, Mohamad Rasli
building UUM Library
collection Institutional Repository
content_provider Universiti Utara Malaysia
content_source UUM Electronic Theses
continent Asia
country Malaysia
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
id my.uum.etd-10196
institution Universiti Utara Malaysia
language en
publishDate 2022
record_format eprints
spelling my.uum.etd-101962025-09-02T07:34:34Z https://etd.uum.edu.my/10196/ Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction Ruziana, Mohamad Rasli 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 NonPeerReviewed text en https://etd.uum.edu.my/10196/1/s94645_01.pdf Ruziana, Mohamad Rasli (2022) Ontology model for zakat hadith knowledge based on causal relationship, semantic relatedness and suggestion extraction. Doctoral thesis, Universiti Utara Malaysia.
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
title 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_short 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
topic BP Islam. Bahaism. Theosophy, etc
BP174 The practice of Islam
url https://etd.uum.edu.my/10196/1/s94645_01.pdf
https://etd.uum.edu.my/10196/
url_provider http://etd.uum.edu.my/