Themes-based classification for Al-Quran knowledge ontology

Al-Quran knowledge representations involved classification of Al-Quran verses for providing better understanding of the readers. In the current era of social media challenges. the representation of knowledge must be understood by human and computer in order to ensure the correctness of Al-Quran semantics are persevered.Current approaches used conventional methods such as taxonomy, hierarchy or tree structure, which only provides a concept definition without linked to other sources of knowledge explanation. This research aims to develop the Al-Quran Ontology by using theme-based classification approach.The ontology model for Al-Quran is developed based on the Al-Quran knowledge theme defined in Syammil Al-Quran Miracle the Reference.The theme-based ontology approach has shown that the Al-Quran knowledge can be classified and presented systematically.This will encourage the development of applications for Al-Quran readers.Moreover, the ontology structure that representing the theme concepts in Al-Quran was reviewed and validated by the domain experts in Al-Quran knowledge

Al-Quran ontology based on knowledge themes

Islamic knowledge is gathered through the understanding the Al-Quran.It requires ontology which can capture the knowledge and present it in a machine readable structured However, current ontology approaches is irrelevant and inaccuracy in producing true concepts of Al-Quran knowledge, because it used traditional methods that only define the concepts of knowledge without connecting to a related theme of knowledge.The themes of knowledge are important to provide true meaning and explanation of Al-Quran knowledge classification.The main aims of this paper are to demonstrate the development of ontology Al-Quran and method used for searching the Al-Quran knowledge using the semantic search approach. Expert review has been applied to validate the ontology model and evaluate the relevance and precision of searching results

New instances classification framework on Quran ontology applied to question answering system

Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. However, this method has a drawback; if the training set amount is small, then the classifier accuracy could decline. Unfortunately, Holy Quran has a small corpus. Based on this problem, our study aims to formulate new instances classification framework for small training corpus applied to semantic question answering system. As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. This algorithm is chosen since it robustness to noisy data and has an excellent achievement to handle small dataset. Furthermore, document processing module on question answering system is used to access instances classification result in Quran ontology

Ontology-based approach for retrieving knowledge in Al-Quran

Information retrieval relies on obtaining relevant data from a set of knowledge resources, such as Al-Quran. Searching can be based on metadata, indexing, or other content-based. Al-Quran is the most widely read book in the world and automating knowledge retrieval from this of religious literature is very challenging. This has led to the development of a number of search applications, which can retrieve knowledge based on keywords. Retrieving the knowledge of Al-Quran ontology includes several fundamental problems, one of which is the lack of accuracy. In most cases, the searching cannot retrieve the relevant concept of knowledge and verses. Current approaches use conventional methods such as taxonomy, hierarchy, or tree structure, which only provide the definition of the concept of themes without linking to the correct knowledge concept of Al-Quran. The main aim of this study is to design a method that uses the ontology approach to search and retrieve relevant verses in Al-Quran. The new approach consists of two stages. The first stage: involves the Al-Quran ontology development based on thematic classification which was implemented using Protégé-OWL. The second stage: involves the development of a search method by using the Jena framework which is based on Java programming languages. The search method allows ontology processing, and performed the searching using the given keywords and retrieve the knowledge pertaining to the keyword. The search approach was evaluated using the Recall and Precision measurements, which shows a high accuracy in retrieving the knowledge of Al-Quran. Furthermore, the ontology classification was evaluated by two experts in Islamic Studies field. This study contributes to the ease of learning and understanding Al-Quran by people of all ages

Semantic-based Ontology for Malay Qur'an Reader

The Quran has been translated into various languages around the world by Muslim experts. One of them is in Malay. There are numerous applications built to facilitate the retrieval of knowledge from the Malay Qur’an. However, there are limited resources and tools that are available or made accessible for the research on Malay Qur’an. Furthermore, there are several issues that need to be considered when dealing with Malay Qur’an translation; such as ambiguities of words, lack of equivalence words between Malay and English or Malay and Arabic, and different structures of word, sentence, and discourse in these two languages. Therefore, this research summarizes the search techniques used in existing research on Qur’an. Moreover, this paper also studied the previous research conducted on Qur’an Semantic Search and Quran Ontology-Based Search focusing on Malay Qur’an. This review helps the research in addressing the general problems and limitations in Malay Qur’an that influence its accessibility. This research proposed the research framework for new semantic based ontology for Malay Qur’an. The final outcome will be an accessible tool that can help a Malay reader to understand the Qur’an in better ways

Ontology-Based Model for Information Retrieval: an Application of Time Nouns in Nahj Al-Balagha

نت دوراً اساسياً في الحياة من خلال كمية واهمية المعلومات التي يوفرها. حاليا، تعتبر إدارة البيانات وإيجاد المعلومات غير دقيقة وذلك لأنها تعتمد على شكل الكلمة وليس معناها. ان عملية تمثيل البيانات والوصول لها من اهم العوامل التي تساهم باسترجاع المعلومات والتغلب على مشكلة التشابه بين المستندات. توجد وسائل لقياس التشابه مختلفة تعمل وفقا ً للوزن والفهرسة والمطابقة. الانطولوجيا هي البنية الأساسية لإدارة البيانات لأنها تستند الى معنى الكلمة والعلاقة بين الكلمات ومجال المعرفة. يقدم هذا البحث اقتراحاً لنموذج نظام دلالي مبني على مجال معرفة محدد (في هذا البحث أسماء الزمن في نهج البلاغة) ويعتمد على المدخلات الدلالية عن طريقة فهرسة محرك البحث باستخدام Vector Space Model (VSM). الهدف من البحث هو تحسين المعلومات الدلالية المسترجعة عن طريق إنشاء استعلام يستند الى المطابقة والتشابه بين كلمات الاستعلام في النظام. هذا العمل مبني على عمل سابق [1]. تم تقييم النظام باستخدام معدل التشابه والدقة والاسترجاع لنتائج التجارب.The internet plays a key role in life through the massive data that it provides. Currently, managing data and finding information on the internet is inaccurate because it depends on the form of the word rather than its meaning. Data representation and access are important factors when it comes to Information Retrieval (IR). In order to overcome the problem of document similarity, there are various similarity measurements in place that function according to weight, indexing and matching. Ontology is a data management infrastructure that gives precedence to the meaning of a word, the relationship between words and the domain of knowledge.  This paper presents a semantic system proposal based on a particular field of knowledge (time nouns) and relies on semantic input by indexing the search engine using a Vector Space Model (VSM). The aim of this work is to improve the retrieved semantic information by constructing a query based on the matching and similarity between the query words in the system. This paper builds upon previous work carried out in the same area [1]. The system was evaluated by using the similarity, average precision and recall of the experiments' results

Knowledge exploration: selected works on Quran ontology development

This paper presents key features and challenges ahead for the development and knowledge retrieval of Quran ontology. Recent studies have made significant advances towards the development of Quran ontology. In the recent past, there have been numerous studies conducted on the application of semantic technologies on Quran. Contribution of this paper is its focus on finding the direction of knowledge exploration in Quran. Several studies on Quran ontology development help us in analyzing its linguistic features. Another dimension where Quran excels is the Knowledge of it. There are few studies that concentrate on retrieval of knowledge from Quran. In this literature review, we have included studies that can help us in developing semantic application for knowledge exploration from Quran. This paper devises challenges mainly focusing towards exploration of knowledge in the Quran and summaries research in this area, discuss key features and open research issues

Quran Ontology: Review On Recent Development And Open Research Issues

Quran is the holy book of Muslims that contains the commandment of words of Allah. Quran provides instructions and guidance to humankind in achieving happiness in life in the world and the hereafter. As a holy book, Quran contains rich knowledge and scientific facts. However, humans have difficulty in understanding the Quran content. It is caused by the fact that the meaning of the searched message content depends on the interpretation. Ontology able to store the knowledge representation of Holy Quran. This paper studies recent ontology on Holy Quran research. We investigate the current trends and technology being applied. This investigation cover on several aspects, such as outcomes of previous studies, language which used on ontology development, coverage area of Quran ontology, datasets, tools to perform ontology development ontology population techniques, approaches used to integrate the knowledge of Quran and other resources into ontology, ontology testing techniques, and limitations on previous research. This review has identified four major issues involved in Quran ontology, i.e. availability of Quran ontology in various translation, ontology resources, automated process of Meronymy relationship extraction, and Instances Classification. The review of existing studies will allow future researchers to have a broad and useful background knowledge on primary and essential aspects of this research field

Systematic Literature Review on Ontology-based Indonesian Question Answering System

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for accurate responses. Secondly, template-based SPARQL query construction, commonly used in Indonesian QA systems, suffers from semantic gaps and inflexibility. Advanced techniques like semantic matching algorithms and dynamic template generation can bridge these gaps and adapt to evolving ontologies. Thirdly, lexical gaps and ambiguity hinder QA systems. Bridging vocabulary mismatches between user queries and ontology labels remains a challenge. Strategies like synonym expansion, word embedding, and ontology enrichment must be explored further to overcome these challenges. Lastly, the review discusses the potential of developing multi-domain ontologies to broaden the knowledge coverage of QA systems. While this presents complex linguistic and ontological challenges, it offers the advantage of responding to various user queries across various domains. This literature review identifies crucial challenges in developing ontology-based Indonesian QA systems and suggests innovative approaches to address these challenges