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

Developing Adaptive Islamic Law Business Processes Models for Islamic Finance and Banking by Text Mining the Holy Quran and Hadith.

Global Islamic finance assets grew from $200 billion to$1.8 trillion (IMF 2015) and is growing faster than the conventional banking sector. A large number of conventional financial institutions, especially banks are moving to an Islamic financial model that\u27s comply with the Shari\u27a Law with little change to current conventional practices (reverse eningineer current business processes) to accommodate the new situation. In this study we will design and develop the business processes for the Islamic financial institutions\u27 (IFIs) products by investigating and collecting information through Islamic literature, surveys and interviews of experts in Islamic jurisprudence, regulators, academic and Islamic finance and banking practitioners. Then we will assess and evaluate the findings by using a Qur\u27anic Financial Corpus and use computational and analytical approaches to mine the Qur\u27an (the Muslim Holy book) and the Hadith (actions and words of the prophet Muhammad peace be upon him) to uncover hidden knowledge on Islamic financial business processes. The knowledge acquired from this investigation will be translated into an Islamic financial process model to be adapted by Islamic and non-Islamic financial institutions. The outcome of this research will influence the future development, growth and diversification of Islamic Financial Services worldwid

Translating selected poysemous words in the Holy Quran into English: An analysis of strategies and procedures

Polysemy refers to those words that have multiple related meanings. In the Qurān, there are numerous polysemous words; therefore, in translating this holy book, the translator will encounter problems in identifying and rendering the intended meaning of the polysemous words. Previous literature has revealed that limited studies have been done to examine how polysemy is translated in the Qurān, namely into English. To bridge this gap, the current study seeks to clarify the governing factors, which help to identify the intended meaning of the polysemous words, in order to propose a logical procedure to transfer the polysemous words in the Qurān. Drawing upon Nida's and Newmark's theories in translation, the study examines the translations of 24 ambiguous senses from 12 selected polysemous words in the Qurān. The samples were selected from four selected translation of the Qurān. Descriptive, interpretive and comparative analyses were carried out in order to achieve its aims. The study reveals that understanding the context, reasons for revelation, perception of the verses surrounding the polysemy, consultation of numerous authentic commentaries and comprehension of the syntactic and grammatical features of the verse are crucial factors in identifying the intended meaning of the polysemous words in the Qurān Polysemy refers to those words that have multiple related meanings. In the Qurān, there are numerous polysemous words; therefore, in translating this holy book, the translator will encounter problems in identifying and rendering the intended meaning of the polysemous words. Previous literature has revealed that limited studies have been done to examine how polysemy is translated in the Qurān, namely into English. To bridge this gap, the current study seeks to clarify the governing factors, which help to identify the intended meaning of the polysemous words, in order to propose a logical procedure to transfer the polysemous words in the Qurān. Drawing upon Nida's and Newmark's theories in translation, the study examines the translations of 24 ambiguous senses from 12 selected polysemous words in the Qurān. The samples were selected from four selected translation of the Qurān. Descriptive, interpretive and comparative analyses were carried out in order to achieve its aims. The study reveals that understanding the context, reasons for revelation, perception of the verses surrounding the polysemy, consultation of numerous authentic commentaries and comprehension of the syntactic and grammatical features of the verse are crucial factors in identifying the intended meaning of the polysemous words in the Qurān. Through the analysis, the study found that the selected translators employed literal and semantic renditions; paraphrasing, descriptive information, communicative translation and transliteration strategies to transfer the meaning of the polysemy. Moreover, the results revealed that the explication, communicative and interpretive strategies are appropriate to convey the intended meaning of the polysemous words in the Qurān. The current study enhances the field of Qurānic translation by proposing concrete procedures to overcome the difficulties in rendering the deep sense of the polysemy in the Holy Qurān. Through the analysis, the study found that the selected translators employed literal and semantic renditions; paraphrasing, descriptive information, communicative translation and transliteration strategies to transfer the meaning of the polysemy. Moreover, the results revealed that the explication, communicative and interpretive strategies are appropriate to convey the intended meaning of the polysemous words in the Qurān. The current study enhances the field of Qurānic translation by proposing concrete procedures to overcome the difficulties in rendering the deep sense of the polysemy in the Holy Qurān

Quranic Topic Modelling Using Paragraph Vectors

The Quran is known for its linguistic and spiritual value. It comprises knowledge and topics that govern different aspects of people’s life. Acquiring and encoding this knowledge is not a trivial task due to the overlapping of meanings over its documents and passages. Analysing a text like the Quran requires learning approaches that go beyond word level to achieve sentence level representation. Thus, in this work, we follow a deep learning approach: paragraph vector to learn an informative representation of Quranic Verses. We use a recent breakthrough in embeddings that maps the passages of the Quran to vector representation that preserves more semantic and syntactic information. These vectors can be used as inputs for machine learning models, and leveraged for the topic analysis. Moreover, we evaluated the derived clusters of related verses against a tagged corpus, to add more significance to our conclusions. Using the paragraph vectors model, we managed to generate a document embedding space that model and explain word distribution in the Holy Quran. The dimensions in the space represent the semantic structure in the data and ultimately help to identify main topics and concepts in the text

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

Statistical Parsing by Machine Learning from a Classical Arabic Treebank

Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the most difficult languages to parse due to rich morphology and free word order. Classical Arabic is the ancient form of Arabic, and is understudied in computational linguistics, relative to its worldwide reach as the language of the Quran. The thesis is based on seven publications that make significant contributions to knowledge relating to annotating and parsing Classical Arabic. Classical Arabic has been studied in depth by grammarians for over a thousand years using a traditional grammar known as i’rāb (إعغاة ). Using this grammar to develop a representation for parsing is challenging, as it describes syntax using a hybrid of phrase-structure and dependency relations. This work aims to advance the state-of-the-art for hybrid parsing by introducing a formal representation for annotation and a resource for machine learning. The main contributions are the first treebank for Classical Arabic and the first statistical dependency-based parser in any language for ellipsis, dropped pronouns and hybrid representations. A central argument of this thesis is that using a hybrid representation closely aligned to traditional grammar leads to improved parsing for Arabic. To test this hypothesis, two approaches are compared. As a reference, a pure dependency parser is adapted using graph transformations, resulting in an 87.47% F1-score. This is compared to an integrated parsing model with an F1-score of 89.03%, demonstrating that joint dependency-constituency parsing is better suited to Classical Arabic. The Quran was chosen for annotation as a large body of work exists providing detailed syntactic analysis. Volunteer crowdsourcing is used for annotation in combination with expert supervision. A practical result of the annotation effort is the corpus website: http://corpus.quran.com, an educational resource with over two million users per year

Graduate Catalog 2014-2015

This catalog is an informative guide to graduate programs and other useful information about university services and policies

Do Machines Replicate Humans? Toward a Unified Understanding of Radicalizing Content on the Open Social Web

The advent of the Internet inadvertently augmented the functioning and success of violent extremist organizations. Terrorist organizations like the Islamic State in Iraq and Syria (ISIS) use the Internet to project their message to a global audience. The majority of research and practice on web‐based terrorist propaganda uses human coders to classify content, raising serious concerns such as burnout, mental stress, and reliability of the coded data. More recently, technology platforms and researchers have started to examine the online content using automated classification procedures. However, there are questions about the robustness of automated procedures, given insufficient research comparing and contextualizing the difference between human and machine coding. This article compares output of three text analytics packages with that of human coders on a sample of one hundred nonindexed web pages associated with ISIS. We find that prevalent topics (e.g., holy war) are accurately detected by the three packages whereas nuanced concepts (Lone Wolf attacks) are generally missed. Our findings suggest that naïve approaches of standard applications do not approximate human understanding, and therefore consumption, of radicalizing content. Before radicalizing content can be automatically detected, we need a closer approximation to human understanding

Language variation in classical and modern standard Arabic: The case of interrogation

This study aims at investigating the functions of interrogatives in classical Arabic and the differences/similarities regarding the syntactic features of interrogatives in classical Arabic and modern standard Arabic. The study depends on gathering data from Classical Arabic (Quran) and Modern Standard Arabic (newspapers). The investigation of this study adopts a qualitative method procedure. The current research focuses on four interrogatives: /kayf/, /matÄ/, /hal/, and /Ê”ayn/. The study identified the functions of interrogatives in classical Arabic: denial, wonder, determination, threat, wish, etc. Furthermore, the study concludes that there are syntactic structures used in both classical Arabic and modern standard Arabic and other structures that are limited to Classical Arabic only or Modern Standard Arabic only. Results of the linguistic analysis of the data suggest that AFL textbooks need to include rhetorical meaning of interrogatives besides the lexical meaning in order to assist foreign learners when dealing with classical texts. It is recommended that the study be replicated on other interrogatives. This may help reveal more functions and syntactic structures associated with specific interrogatives