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

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

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

A novel dataset for quranic words identification and authentication

Quran is the holy book for Muslims around the world. For the past fourteen centuries after its revelation, ithas been preserved in all possible ways from any distortions. The huge increase in Internet usage and the spread of digital media lead to the development of many websites, services, and applications related to Quran. These efforts include the conversion of Quranic verses, translations, explanations,tafseer and other Quranic sciences into digital formats. Some of these efforts are foundless authentic. The authentication dependson correct identification of Quranic words in the text. In this paper, we introduce a novel dataset for Quranic words identification and authentication. The proposed dataset contains more than 93,000 samples with64 features for each extracted in numerical form.The validation tests of the proposed dataset resulted high accuracy average

Topic identification using filtering and rule generation algorithm for textual document

Information stored digitally in text documents are seldom arranged according to specific topics. The necessity to read whole documents is time-consuming and decreases the interest for searching information. Most existing topic identification methods depend on occurrence of terms in the text. However, not all frequent occurrence terms are relevant. The term extraction phase in topic identification method has resulted in extracted terms that might have similar meaning which is known as synonymy problem. Filtering and rule generation algorithms are introduced in this study to identify topic in textual documents. The proposed filtering algorithm (PFA) will extract the most relevant terms from text and solve synonym roblem amongst the extracted terms. The rule generation algorithm (TopId) is proposed to identify topic for each verse based on the extracted terms. The PFA will process and filter each sentence based on nouns and predefined keywords to produce suitable terms for the topic. Rules are then generated from the extracted terms using the rule-based classifier. An experimental design was performed on 224 English translated Quran verses which are related to female issues. Topics identified by both TopId and Rough Set technique were compared and later verified by experts. PFA has successfully extracted more relevant terms compared to other filtering techniques. TopId has identified topics that are closer to the topics from experts with an accuracy of 70%. The proposed algorithms were able to extract relevant terms without losing important terms and identify topic in the verse

Atti del IX Convegno Annuale dell'Associazione per l'Informatica Umanistica e la Cultura Digitale (AIUCD). La svolta inevitabile: sfide e prospettive per l'Informatica Umanistica

Proceedings of the IX edition of the annual AIUCD conferenc

Atti del IX Convegno Annuale AIUCD. La svolta inevitabile: sfide e prospettive per l'Informatica Umanistica.

La nona edizione del convegno annuale dell'Associazione per l'Informatica Umanistica e la Cultura Digitale (AIUCD 2020; Milano, 15-17 gennaio 2020) ha come tema “La svolta inevitabile: sfide e prospettive per l'Informatica Umanistica”, con lo specifico obiettivo di fornire un'occasione per riflettere sulle conseguenze della crescente diffusione dell’approccio computazionale al trattamento dei dati connessi all’ambito umanistico. Questo volume raccoglie gli articoli i cui contenuti sono stati presentati al convegno. A diversa stregua, essi affrontano il tema proposto da un punto di vista ora più teorico-metodologico, ora più empirico-pratico, presentando i risultati di lavori e progetti (conclusi o in corso) che considerino centrale il trattamento computazionale dei dati

Implementation of Communication in Improving the Quality of Education

This paper aims to examine the implementation of communication in improving the quality of education. Communicating will determine the ability to succeed or not the quality of education and quality education institutions. Therefore, the progress of an institution or institution depends on the ability to carry out communication between the leader and its members as well as the interaction and communication that occurs in it. For this reason, this article discusses the role of communication in the management of Islamic education. The method used is the literature study method. Reference materials are sources and techniques for testing the validity of the data