- Email: firstname.lastname@example.org
- Thesis title: Qur’anic semantic search tool based on ontology of concepts
My name is Mohammad Alqahtani, a PhD student at school of computing - University of Leeds, UK. During the Last three years, I worked as an Information Technology lecturer, at King Abdulaziz University (KAU) in Saudi Arabia; teaching introductory computer science courses for undergraduate students. These courses are: introduction to programming, introduction for computer sciences, Data Structures & Algorithms in Java and Design & Analysis of Algorithms.
I began my higher education from bachelors program, with my Bachelors Degree of Sciences in Computer Science from King Fahd University of Petroleum and Minerals – Saudi Arabia. During this degree, I studied the fundamentals and principles of programming, algorithms, Database, network and software engineering. Additionally, numerous courses in Mathematics, Physics and Chemistry were studied as well.
After the completion of my Bachelors Degree of Sciences in Computer Science, I continued my studies by applying for the Master’s program. At the end of last year, 2011, I was awarded the Master’s Degree of science in Computer Science, with distinction from University of Hertfordshire, in the UK. During the master’s program, my focus was on software engineering and subjects pertaining to web development. Additionally, I studied an intensive course about Network Systems Administrator. Moreover, my Master’s project was on an online Lecturer appointment system for MSc Project students. This project is a web based system, which used a single login ID technique.
Five years prior to the starting of my MSc, I used to work at a Training Centre of Saudi Electricity Company (SEC), as a computer trainer. My responsibilities were to train the SEC’s employees on the Microsoft Applications, Information Management Systems and Human Resources courses of SAP (Systems, Applications and Products). Additionally, I worked as programmer, system analyst and E-learning system administrator.
The Holy Quran is the most important resource for the Islamic sciences and Arabic Language. Additionally, this holy book contains knowledge on diverse topics such as life and history of humanity, and scientific knowledge. As a consequence, many Qur’anic search applications have been built to facilitate the retrieval of knowledge from the Quran. Examples of these web applications are Qurany , Quran Explorer , Tanzil , and Qur’anic Arabic corpus .
The techniques used to retrieve information from Qur’an can be classified as semantic-based and text-based. The existing semantic search techniques are: ontology-based (concepts) , Synonyms-set , and Cross Language Information retrieval (CLIR) . On the other hand, text-based techniques are Keyword matching, and Morphological-based . The majority of Qur’anic search tools employ a keyword search technique while minority of tools use a semantic technique. There are several deficiencies with the verses (Aya’at) retrieved for a query using existing search tools. These problems are: some irrelevant verses are retrieved, some relevant verses are not retrieved, or the sequence of retrieved verses is not in the right order . The significant reasons for unsatisfactory searching results are: absence of an accurate and comprehensive resource for Islamic ontology, and neglecting some theories of information retrieval .
This project aims to construct a useful Qur’anic search tool by employing both text-based techniques, and semantic search techniques. The research will answer two questions: Is it possible to implement a useful search tool based on Qur’anic ontology, and Qur’anic datasets? And How to assess the efficiency and accuracy of an existing Qur’anic ontology? Furthermore, the main project objectives are to understand the problem by evaluating existing Qur’anic semantic search, assess the current Islamic ontologies and find out how these ontologies can be developed, and find the latest search techniques to employ in a Qur’anic search engine.
Research groups and institutes
- Artificial Intelligence