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International Journal of Engineering & Technology, 7 (4.15) (2018) 80-86
International Journal of Engineering & Technology
Website: www.sciencepubco.com/index.php/IJET
Research paper
A Systematic Review on Semantic-based Ontology for Quranic
Knowledge
Asma Salsabila Muhmad Rusli1, Farida Ridzuan1*, Zulkifly Mohd Zaki1*, M Norazizi Sham Mohd Sayuti1*,
Rosalina Abdul Salam1*
1Faculty of Science and Technology, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malay-
sia
2Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sem-
bilan, Malaysia
*Corresponding author E-mail: farida@usim.edu.my; zulkifly@usim.edu.my; azizi@usim.edu.my; rosalina@usim.edu.my
Abstract
The Holy Quran ontology models are gaining popularity among researchers due to people’s demands in understanding this divine book.
Due to this, there are many studies and research have been conducted in this area to facilitate people’s understanding of the Quran. The
Quran knowledge is represented conforming to an ontology within a system framework. This also includes various concepts that are
interrelated with the others. From the literature, however, the existing Quranic ontology models do not cover all concepts in the Quran,
which limit them to domains such as place nouns, themes, pronouns, antonyms and Islamic knowledge in the Quran. Thus, this research
aims to identify relevant research works from various electronic data sources using systematic literature review (SLR) method to provide
a comprehensive review of this area. This paper presents a systematic review of the literature related to the existing ontology models,
where it leads to disseminating the correct knowledge of the Quran using semantic technologies.
Keywords: Ontology; Quran; Semantic; Systematic Review.
1. Introduction
Ontology is a knowledge representation of a collection of facts
and concepts about certain domain and describes how those con-
cepts interrelated with each other. It plays an important role in
semantic web, information extraction, artificial intelligence, natu-
ral language processing, and knowledge management etc. [1]. It is
relevant for knowledge-based systems as it can capture the
knowledge, process and depict the interrelations of the domains
and concepts in a particular ontology model. Currently, there are
many artificial intelligence models of the Quran incorporating
ontology to explore its divine knowledge such as [2-5]. These
intelligent systems were developed to answer questions regarding
underlying knowledge in the Quran. Quran is comprised of Arabic
scripts, complex structure and lexicons that convey implicit mean-
ings using different contexts. Its verses and words have ambigu-
ous interpretations despite the same structure of the word because
Arabic words could have varied meanings only with slight chang-
es of diacritics. For example, ‘’represents two distinct words:
‘’ means paradise, and ‘’ means ghosts [6]. Researchers
have proposed different types of approaches and parameters in
developing and evaluating the Quran ontology models in terms of
their performances and efficiency. Recently, studies such as [7-8]
have been broadened to other fields involving Arabic vocabulary.
The semantic-based approach has been applied in many ontology
implementations within Quranic domains. This method has been
proven as effective compared to keyword search. For example, in
[9-11] implemented semantic search techniques which is the re-
trieved results match with a user’s query that are related to certain
concepts and synonym-sets that return all synonym results that
match with the query words. However, current research is limited
to a particular concept and domains resulting in challenges in cap-
turing and representing the knowledge. This can limit the accuracy
of search results and in the case where the ontologies are not
aligned to each other, inaccurate and incomprehensible resources
for the ontologies may result [2, 12].
In this paper, the existing ontology models of Quran are studied
and presented using Systematic Literature Review (SLR) inspired
from [13]. This has been applied in various fields such as software
engineering [14], information system [15] and networking [16].
SLR is a protocol that identify, evaluate and interpret all available
research relevant to the research questions, or the topic of inter-
ests. SLR is undertaken to review and identify any gaps and limi-
tations in the current studies.
The objectives of this systematic review are; 1) to review the ex-
isting implementation of ontologies of the Quran knowledge, 2) to
examine the existing models used to develop the ontology and 3)
to underline any limitations for proposing future studies in Quran
ontology. The rest of this paper is organized as follows: the outline
and details of research method are presented in Section 2. Section
3 explains the results from this study followed by the limitation of
existing studies in Section 4. Finally, conclusion and future re-
search directions are discussed in Section 5.
2. Methodology
This systematic literature review (SLR) is presented using formal
systematic literature review process by [13]. This process de-
scribes a protocol on generalizing the vast number of articles by
answering the research questions. This unbiased search is one
International Journal of Engineering & Technology
81
factor that differentiates systematic review from traditional review
as they must comply with the research questions and criteria. This
section describes the outline of the review process as illustrated in
Figure 1. These stages are proceeding sequentially to retrieve po-
tential primary articles. The first step involves a process of formu-
lating research questions. Next, the search process is conducted
which includes sources of selection and search keywords. This
process aims to identify the existing works and potentially rele-
vant studies in this area. The next step is inclusion-exclusion crite-
ria in assenting relevant primary articles. Then, the information is
extracted and organized based on quality assessment conditions.
Fig. 1: SLR Process.
The following sub-sections define the methods used in conducting
this review. The relevant primary sources are summarized and
presented in the next section.
2.1. Research Questions
In order to evaluate the current ontology implementation in Quran
and evaluation parameters used in the previous research, this study
investigates the research questions as shown in Table 1. The first
research question studies the current trend of implementing ontol-
ogy in representing semantic Quran knowledge (RQ1). To answer
RQ1, a number of published journals and conference proceedings
dated from 2012 to 2017 were reviewed. The main idea and re-
search problems in the studies were analysed. Two sub-questions
were derived to answer RQ2, which is analysing methods and
models proposed by researchers. RQ3 leads to the answer to the
limitation of the existing research on semantic Quran ontological
models. This provides a new direction in designing an ontology
model.
Table 1: Research Questions of SLR
No.
Research Questions
RQ1
What is the existing research and studies on implementation of
semantic-based Quran ontology model?
RQ2
How ontology models are reviewed in the previous works?
RQ2.1: What are the methods used to develop the semantic-based
Quran ontology model?
RQ2.2: What are the techniques and metrics used to evaluate the
ontology?
RQ3
What are the limitations of the existing research on semantic-
based Quran ontology model?
2.2. Search Process
This process is conducted to identify any potential relevant studies
regarding the existing literatures, based on the research questions
above. The selection process undertakes a thorough four-step as
shown in Figure 2. The articles were retrieved from five digital
databases as listed below:
Google Scholar
IEEE Xplore Digital Library
Research Gate
Science Direct
Springer Link
Fig. 2: Search Process of Systematic Review
Based on Figure 2, the activities involved for search process start
with the articles’ search, which is carried out using keywords
search in the article title and abstract. Primary keywords “Ontolo-
gy” and “Semantic” and “Quran” or secondary keyword “Ontolo-
gy” and “meaning” and “Arabic” were used in the search criteria
in the digital databases selected. These keywords define the titles
and contents of the articles which resulting in retrieving articles
related to semantic Quran ontology models. The secondary key-
words consider alternative search strings to obtain other relevant
articles. Title and abstracts of the retrieved articles were down-
loaded. Then, thorough reading and critical review were carried
out to select relevant articles relating to Quranic ontology models.
Lastly, primary articles were sorted out following the inclusion
and exclusion criteria tabulated in Table 2 and Table 3 in the next
subsection.
2.3. Inclusion-Exclusion Criteria
The primary articles were selected based on the inclusion and
exclusion criteria. The criteria are outlined manually to attain the
requirements of primary articles referring to research questions.
These criteria are vital in approving primary articles and ruling out
any irrelevant papers. This can be done by thorough reading and
scrutinizing the criteria. Table 2 presents the inclusion criteria that
assent the primary articles’ selection. Meanwhile, papers that ful-
fill the exclusion criteria in Table 3 were excluded from this study.
Table 2: Inclusion Criteria
No.
Inclusion Criteria
IC1
The ontology of semantic-based Quran knowledge must be the
major topic of discussions in the articles.
IC2
Articles do present and outline the methods and parameters used
in constructing the ontology.
Table 3: Exclusion Criteria
No.
Exclusion Criteria
EC1
Articles’ contents not related to the ontology of semantic context
of Quran knowledge.
EC2
Articles do not outline the methods and parameters used to repre-
sent the ontology models.
EC3
Duplicate articles from the same researches and topics.
EC4
Publications that provide ambiguous report, e.g. only abstract
presented.
2.4. Data Extraction and Quality Assessment
The quality of assessment conditions (Table 4) was formulated to
analyse whether the articles’ context of the studies is complete and
can be practically used. This is to ensure the quality of the selected
primary articles. The conditions tabulated below are inspired by
[14, 16] in assessing the quality of their SLR reviews. These con-
ditions weight the importance of each study resulting the quality
differences in terms of points. Furthermore, they can minimize
any invalid and ambiguous articles. The points used for the an-
swers are Yes = 1, Partially = 0.5 and No = 0 point. Articles that
comply with the conditions and weight 3.5 points and above will
be signified as primary articles. From a thorough assessment, the
primary articles have been finalised and tabulated in Table 5.
3. Results and Discussion
The selected primary articles were discussed and summarised
below, followed by the results according to its respective research
questions.
3.1. Primary Articles Selection
First, preliminary search is conducted using the defined keywords
from the digital databases and a sum of 138 articles, journals,
theses, reports and proceedings has been collected to extract useful
82
International Journal of Engineering & Technology
information such as title, year of publication, authors and methods
proposed. The inclusion and exclusion criteria, sort out the articles
and return 58 articles. Hence, only 58 primary articles were select-
ed for this review as they were relevant and comply with the crite-
ria stated.
Table 4: Quality Assessment Conditions.
No.
Conditions
Answer
QA1
The objectives of the research are clearly stated.
Yes/Partially/No
QA2
The approach used to construct the ontology is described and discussed methodically.
Yes/Partially/No
QA3
The results presented are thoroughly explained and evaluated.
Yes/Partially/No
QA4
The information required can be extracted directly from the study.
Yes/Partially/No
Table 5: Primary articles
Title
Points
The Noble Quran Arabic Ontology: Domain Ontological Model and Evaluation of Human and Social Relations
4
Semantic Hadith: Leveraging Linked Data Opportunities for Islamic Knowledge
4
Arabic Quranic Search Tool Based on Ontology
3.5
Developing an Ontology of Concepts in the Qur'an
3.5
Domain-specific Ontology-based Approach for Arabic Question Answering
3.5
Cross-Domain Semantic Web Model for Understanding Multilingual Natural Language Queries: English/Arabic Health/Food Domain Use
Case
3.5
Applying Ontological Modeling on Quranic Nature Domain
3.5
Al-Bayan: A Knowledge-based System for Arabic Answer Selection
4
Semantically Answering Questions from the Holy Quran
4
Semantic Arabic Information Retrieval Framework
4
Ontology-based Model for Arabic Lexicons: An Application of the Place Nouns in the Holy Quran
3.5
QuranAnalysis: A Semantic Search and Intelligence System for the Quran
4
Semantic Quran
4
Ontology-based Approach for Retrieving Knowledge in Al-Quran
4
ISWSE: Islamic Semantic Web Search Engine
4
Arabic Anaphora Resolution: Corpus of the Holy Quran Annotated with Anaphoric Information
4
Creation and Populating of an Islamic Knowledge Ontology using Extraction Pattern Bootstrapping
3.5
Using Association Rules for Ontology Extraction from a Quran Corpus
3.5
Object-based Knowledge Representation of Female Related Issues from the Holy Quran
4
Azhary: An Arabic Lexical Ontology
4
Automated Semantic Query Formulation for Quranic Verse Translation Retrieval
4
Using Ontology for Associating Web Multimedia Resources with the Holy Quran
3.5
Rules and Natural Language Pattern in Extracting Quranic Knowledge
4
An Ontology Engineering Approach with a Focus on Human Centered Design
3.5
Quranic Verse Extraction based on Concepts using OWL-DL ontology
3.5
Ontological Knowledge Management System of Islamic Concepts
3.5
An Experience of Developing Quran Ontology with Contextual Information Support
3.5
Al-Quran Themes Classification using Ontology
3.5
Quranic-based Concepts: Verse Relations Extraction using Manchester OWL Syntax
3.5
QurAna: Corpus of the Quran Annotated with Pronominal Anaphora
4
RQ1: What is the existing research and studies on implemen-
tation of the Quran ontology model?
The existing studies have been analysed based on the quantities of
articles published throughout the years. The search was restricted
to publications between year 2012 to 2017 as illustrated in Figure
3. A lot of researches have been conducted in leveraging ontologi-
cal modelling using semantic web technologies in the field of
Holy Quran. As shown in Figure 3, the demand of Islamic
knowledge of the Holy Quran is progressively increase from 2012
until 2016. In the semantic field, research works are mostly aimed
to analyse the lexical forms of Holy Quran manuscript, concepts,
domains and themes. Based on the quality assessment conditions
in Table 4, only 30 articles with the score of 3.5 and above were
used to answer the following research questions RQ2.
RQ2: How ontology models are reviewed in the previous
works?
The sub questions RQ2.1 and RQ2.2 answer the methods and
parameters used to analyse and construct the ontology of Quranic
modelling.
Fig. 3: Number of Publications throughout 2012 to 2017
RQ2.1: What are the methods used to develop the semantic-
based Quran ontology model?
In the study conducted by [13], the ontology models were ana-
lysed and synthesised descriptively based on the techniques, types
of ontology, datasets and domain coverage. The data synthesis
extracted the information about the related studies and tabulate
them to highlight the similarities and differences between the
study outcomes [13]. Table 6 presents the types of techniques used
in constructing Holy Quran ontology models. This paper analyses
and categorises the methods into two groups, which are Quran
concepts/domains and Islamic knowledge.
International Journal of Engineering & Technology
83
Table 6: Ontology Model’s Methods.
Methods
Ontology Model
Quran concepts/domains
[9, 17-34]
Islamic knowledge
[6-8]
RQ2.2: What are the techniques and metrics used to evaluate
the ontology?
This paper focuses on categorising the evaluation techniques from
[35]. According to [35], there are four types of ontology evalua-
tion techniques, which is, gold standard, application-based, user-
based and data driven. Previous researchers have applied these
techniques in their studies to evaluate and measure the proposed
ontology. The techniques for evaluation are presented in Table 7.
Table 7: Evaluation Techniques.
Techniques
Ontology Model
Gold standard
[3, 8, 25]
Application-based
[5, 7, 36, 25, 33]
User-based
[5, 8-9, 17-19, 21-23], [26-29]
Data-driven
[17, 21, 24, 34]
For the first technique, gold standard means to compare the pro-
posed ontology against the other established ontology (IEs). For
example, in [3] contrasted their proposed Azhary, an Arabic Lan-
guage lexical ontology against Arabic WordNet (AWN) in terms
of words semantic meanings and relations. Meanwhile, in [25]
compared his QuranAnalysis (QA) with the other twelve ontolo-
gies according to the nine list criteria proposed in [37]. Applica-
tion-based is measured by the functionality of the ontology onto
an actual software program or a use-case scenario (application).
Both [7, 33] implemented their ontologies using Protégé to repre-
sent the knowledge and manage the class hierarchy and relation-
ships. In [25] integrated his QA Ontology into QA website to add
more functionalities and smartness, and in [30] used PROMPT
system to compare the results obtained.
Apart from that, there is also a user-based evaluation where hu-
man experts assess on how well the ontology meets a set of prede-
fined criteria, standards and requirements. The ontology models
were evaluated manually by experts and query run. SPARQL,
OWL as well as DL languages is used to determine the correct
query and check whether all retrieved classes, sub-classes, indi-
viduals and relations are accurate and valid throughout the process.
Some sample tests are executed using the query and the results are
shown in the output. Other than that, experts from that field also
evaluate the proposed model by comparing the results and con-
ducted a manual check [18-19, 26]. The performance, correctness
and effectiveness of the ontology models are measured manually
using the metrics of Precision (P), Recall (R) and F-measure. (P)
refers to the correctness of retrieval answers that are relevant to
the query, while (R) refers to the relevant answers that are suc-
cessfully retrieved. Numerous researchers applied these measure-
ments in their studies to evaluate their ontology models [5, 8-9, 24,
27, 32, 34]. These measurements are calculated in percentages,
where high percentage indicates the correctness of the retrieved
answers. On the other hand, some algorithms are used as evalua-
tion metrics. For example, in [21] applied the Apriori algorithm to
mine the association rules representing the relations between clas-
ses of concepts in the Quran ontology. Other than that, in [17]
proposed QurAna, which a large corpus is created from the Quran
that annotated the verses with pronominal anaphora (personal
pronouns) with their antecedents. They measured the verses dis-
tance using the Vector Space Model (VSM). The distance between
query terms and document is measured where the cosine of the
angle (verse distance) between them is compared. Then, each term
is weighted using term frequency–inverse document frequency (tf-
idf) metric inspired from [38]. The resulting weight is normalised
and the distance is calculated to measure the similarity between
them. The similarity value lies between zero (0) and one (1),
where 0 indicates no similarity, and 1 indicates identical matching.
Last but not least, data-driven can be performed by comparing the
ontology against a corpus based on the ontology coverage and the
domain of the ontology models. In [17] compared their QurAna
ontology against the other seven available corpora annotated with
anaphora resolution. In [21, 34] evaluated their ontologies to a
collection of Quran chapters that related to the stories of the
prophets. They used a specific corpus characterised by the special-
isation of its domain (stories of the prophets). In [24] evaluated the
capabilities of their ontology models by comparing against nine
Quran search engines in terms of certain keywords such as Educa-
tion, Christian, Heritage, Boat, Hell, Miracle of Jesus and Flood.
These research works on Quran ontology models are summarised
in Table 8 comprising all details, including methods, models re-
search focus and evaluation techniques. This table depicts the
outline of RQ1 and RQ2’s answers.
Table 8: Research works on Quran Ontology
Title
Author
Year
Method
Model
Research Focus
Evaluation
The Noble Quran Arabic
Ontology: Domain Onto-
logical Model and Evalua-
tion of Human and Social
Relations
Tashtoush, Yahya M., Majd R. Al-
Soud, Reema M. AbuJazoh, and
Manar Al-Frehat
2017
Quran concepts/
domains
Noble Quran
ontological
model
Human and So-
cial relations in
Quran
User-based
Developing an Ontology of
Concepts in the Qur'an
Ahmed, Rasha, and E. S. Atwell
2016
Quran concepts/
domains
Quran ontolo-
gy model
Abstract concepts
from various
sources
Application-
based, User-
based
Domain-specific Ontology-
based Approach for Arabic
Question Answering
Sheker, Mustefa, Saidah Saad,
Rehab Abood, and Mohanaad
Shakir
2016
Islamic
knowledge
Automatic
Question
Answering
System
Islamic fatwas
(prayer)
Gold standard,
User-based
Applying Ontological
Modeling on Quranic Na-
ture Domain
Sadi, ABM Shamsuzzaman,
Towfique Anam, Mohamed
Abdirazak, Abdillahi Hasan
Adnan, Sazid Zaman Khan, Mo-
hamed Mahmudur Rahman, and
Ghassan Samara
2016
Quran concepts/
domains
Ontological
model
Nature concepts
in Quran
User-based
Al-Bayan: A Knowledge-
based System for Arabic
Answer Selection
Mohamed, Reham, Maha Ragab,
Heba Abdelnasser, Nagwa M. El-
Makky, and Marwan Torki
2015
Islamic
knowledge
Al-Bayan
Islamic sciences
Application-
based, User-
based
Semantically Answering
Questions from the Holy
Quran
Shmeisania, Hashem, Samir
Tartirb, Ammar Al-Na’ssaanc, and
Moath Najid
2015
Quran concepts/
domains
Quranic On-
tology
Quranic concepts
related to Prophet
Muhammad
Data-driven
Ontology-based model for
Arabic lexicons: An appli-
cation of the Place Nouns
Alromima, Waseem, Ibrahim F.
Moawad, Rania Elgohary, and
Mostafa Aref
2015
Quran concepts/
domains
Place Nouns
Ontology
Place nouns in
Quran
User-based
84
International Journal of Engineering & Technology
Title
Author
Year
Method
Model
Research Focus
Evaluation
in the Holy Quran
QuranAnalysis: A Seman-
tic Search and Intelligence
System for the Quran
Ouda, Karim
2015
Quran concepts/
domains
QuranAnalysis
All chapters in
Quran
Gold standard
Semantic Quran
Sherif, Mohamed Ahmed, and
Axel-Cyrille Ngonga Ngomo
2015
Quran concepts/
domains
Semantic
Quran Ontol-
ogy
All chapters in
Quran
User-based
ISWSE: Islamic Semantic
Web Search Engine
Ishkewy, Hossam, and Hany Harb
2015
Quran concepts/
domains
Islamic Ontol-
ogy
Islamic concepts
Data-driven
Arabic Anaphora Resolu-
tion: Corpus of the Holy
Quran Annotated with
Anaphoric Information
Seddik, Khadiga M., Ali Farghaly,
and Aly Aly Fahmy
2015
Quran concepts/
domains
Holy Quran
scripts anno-
tated with
anaphoric
information
Personal pro-
nouns in Quran
User-based
Creation and Populating of
an Islamic Knowledge
Ontology using Extraction
Pattern Bootstrapping
Ghanem, Mohamed, Abdelaaziz
Mouloudi, and Mohammed
Mourchid
2015
Islamic
knowledge
OntoShari’a
Hadith books’
concepts (Sahih
Muslim and Sahih
Al-Bukhari)
Application-
based
Using Association Rules
for Ontology Extraction
from a Quran Corpus
Harrag, Fouzi, Abdullah Al-
Nasser, Abdullah Al-Musnad,
Rayan Al-Shaya, and Abdulmalik
Al-Salman
2014
Quran concepts/
domains
Quran ontolo-
gy
Prophets stories
in Quran
Data-driven,
User-based
Object-based Knowledge
Representation of Female
Related Issues from the
Holy Quran
Ku-Mahamud, Ku Ruhana, Aniza
Mohamed Din, Noraziah Che Pa,
Faudziah Ahmad, Wan Hussain
Wan Ishak, Farzana Kabir Ahmad,
and Roshidi Din
2014
Quran concepts/
domains
Object-based
knowledge
representation
using Seman-
tic Network
and Conceptu-
al Graph
Female related
issues in Quran
User-based
Azhary: An Arabic Lexical
Ontology
Ishkewy, Hossam, Hany Harb, and
Hassan Farahat
2014
Arabic lexicon
Azhary ontol-
ogy
Arabic language
Gold standard,
Application-
based
Using Ontology for Asso-
ciating Web Multimedia
Resources with the Holy
Quran
Abdelhamid, Yasser, Mostafa
Mahmoud, and Tarek M. El-Sakka
2013
Quran concepts/
domains
Holy Quran
(HQ) Ontolo-
gy
Multimedia-
enabled Holy
Quran (HQ)
browser
Application-
based
Rules and Natural Lan-
guage Pattern in Extracting
Quranic Knowledge
Saad, Saidah, S. Azman Mohd
Noah, Naomie Salim, and Hakim
Zainal
2013
Quran concepts/
domains
Quranic On-
tology
Knowledge of
Quranic English
translation texts
User-based
Quranic Verse Extraction
based on Concepts using
OWL-DL ontology
Yauri, Aliyu Rufai, Rabiah Abdul
Kadir, Azreen Azman, and Masrah
Azrifah Azmi Murad
2013
Quran concepts/
domains
Quran ontolo-
gy model
Concepts in
Quran
User-based
Ontological Knowledge
Management System of
Islamic Concepts
Ali, Hayat
2013
Quran con-
cepts/domains
Ontological
model
Semantic rela-
tionship between
different verses
Application-
based, User-
based
An Experience of Develop-
ing Quran Ontology with
Contextual Information
Support
Iqbal, Rizwan, Aida Mustapha,
and Zulkifli Mohd. Yusoff
2013
Quran concepts/
domains
Quran ontolo-
gy
Juz ‘Amma
User-based
Al-Quran Themes Classifi-
cation using Ontology
Ta'a, Azman, Syuhada Zainal
Abidin, Mohd Syazwan Abdullah,
Mat Ali, Abdul Bashah, and Mu-
hammad Ahmad
2012
Quran concepts/
domains
Al-Quran
Ontology
Model
Themes in Quran
(Iman and
Akhlaq)
User-based
Quranic-based Concepts:
Verse Relations Extraction
using Manchester OWL
Syntax
Yauri, Aliyu Rufai, Rabiah Abdul
Kadir, Azreen Azman, and Masrah
Azrifah Azmi Murad
2012
Quran concepts/
domains
Quran ontolo-
gy model
Concepts in
Quran
User-based
QurAna: Corpus of the
Quran Annotated with
Pronominal Anaphora
Sharaf, Abdul-Baquee M., and
Eric Atwell
2012
Quran concepts/
domains
Ontological
model
Pronominal
anaphora (pro-
nouns) in Quran
User-based,
Data-driven
4. Research Limitation
The research limitation will be answered by RQ3.
RQ3: What are the limitations of the existing research
on semantic-based Quran ontology model?
This is a big challenge as arrangements of Quran verses are not
according to the topics. Current studies limit itself to a particular
domain or up to certain specific verses. The search areas are lim-
ited and constricted to a particular domain or concepts only rather
than the whole Quran itself. The ontology will be unaligned be-
tween verses with the same concepts, which will decrease the
accuracy of the results (verses) and false information retrieved.
Information retrieval
The limitations of the existing Quran ontology models are re-
trieving all requested information from the queries. In the
Quran, several words may have different syntax, located in
different locations and chapters, but they carry the same
meaning and related semantically. For example, (night)
and (evening) are related as they are part of (time).
Moreover, irrelevant verses are retrieved from the input que-
ry. This will cause misunderstandings of the meaning behind
the Quran verses. The main causes are these semantic search
tools do not cover all concepts in the Holy Quran leading to
International Journal of Engineering & Technology
85
inaccurate results [2]. This can affect the accuracies of the re-
trieved results.
Quran knowledge representation
Most Muslims are ignorant of the deeper meanings in the
Quran and do not understand the text correctly, in spite of
learning the sounds of the verses [39].
In this Quran computation field, a new model that represents the
Quran contextual knowledge that can bring an accurate and valid
contextual information retrieval with covering the whole scopes,
domains and relationships within the Quran is required.
5. Conclusion
A systematic literature review was conducted in this paper to ana-
lyse the issues on the development of semantic-based ontology
model in the Holy Quran. This paper has explained the process of
selecting and reviewing literature according to Kitchenham style.
SLR helps researchers in analysing and focusing on selected pri-
mary studies from a broad field. This can be carried out by ensur-
ing the papers comply with the research questions, criteria and
quality conditions. The literature review covered the techniques
and parameters used to evaluate the Quran ontology models. This
paper observed the methodology and evaluation parameters in
constructing the ontology model. From the studies conducted,
knowledge in the Quran has been explored and summarized by
various researchers. However, they are inadequate coverage of
Quran domains and concepts within the ontology models. This can
limit the accuracy of the results retrieved and lead to people mis-
understandings. Furthermore, the key features of this area and the
research issues have been discussed. Lastly, further investigations
needs to be done to review the issues counterparts. Thus, a Quran
ontology model that covers all domains that highlight the whole
contextual Quran knowledge would give people a clearer under-
standing of this divine book. Semantic technology also can pro-
vide deeper meaning and context of the knowledge by interrelat-
ing the concepts in the Quran.
Acknowledgement
This work was supported by the Universiti Sains Islam Malaysia
(USIM) and Ministry of Higher Education, Malaysia
(USIM/TRGS02_PROJEK01/ISI/59/50416).
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