Abstract

This study presents a review on the computer based academic researches related to Quran. The main motivation of the paper is because of the growing interest in the Quran knowledge globally, where today we are witnessing several researches on Quran being the main source of knowledge and law for Muslims. Today, computer based research on the Quran is being conducted globally by both Muslims and non-Muslims from various institutions. The study will give an up to date on computer based researchers conducted previously and will assist in furthering up researches in the area.

Keywords:

Data mining, information retrieval, knowledge representation, linguistic, Quran, semantic,

References

1. Abbas, N.H., 2009. Quran 'search for a concept' tool and website. M.Sc. Thesis, The University of Leeds, UK.
   
2. Al-Gharaibeh, A., A. Al-Taani and I. Alsmadi, 2011. The usage of formal methods in Quran search system. Proceeding of the ICICS 2011. Retrieved from: http://www.icics.info/icics/Proceeding/ICICS.paper/61.pdf.
   Direct Link
3. Ali, I., 2012. Application of a mining algorithm to finding frequent patterns in a text corpus: A case study of the Arabic. Int. J. Softw. Eng. Appl., 6(2012): 127-134.
   
4. Aliyu, R.Y., A.K. Rabiah, Azreen Azman and A.A.M. Masrah, 2013. Quranic verse extraction base on concepts using OWL-DL ontology. Res. J. Appl. Sci. Eng. Technol., 6(23): 4492-4498.
   
5. Aliyu, R.Y., A.K. Rabiah, A. Azreen and A.A.M. Masrah, 2014. Semantic web application for historical concepts search in Al-Quran. Int. J. Islam. Appl. Comp. Sci. Technol., 2(2): 1-7.
   
6. Al-Yahya, M. and H. Al-Khalifa, A. Bahanshal, I. Al-Odah and N. Al-Helwah, 2010. An ontological model for representing semantic lexicons: An application on time nouns in the Holy Quran. Arabian J. Sci. Eng., 35(2): 21.
   
7. Baqai, S., A. Basharat, H. Khalid, A. Hassan and S. Zafar, 2009. Leveraging semantic web technologies for standardized knowledge modelling and retrieval from the Holy Quran and religious texts. In: ACM Special Interest Group on Artificial Intelligence. Proceedings of the 7th International Conference on Frontiers of Information Technology, New York.
   
8. Bettina, F., G. Giorgio, G. Georg and L. Thomas, 2010. Semantic web search based on ontological conjunctive queries. Lect. Notes Comput. Sc., 5956: 153-172.
   CrossRef    
9. Christopher, D. and P. Hinrich, 2009. Introduction to Information Retrieval. Cambridge University Press, New York.
   
10. Dror, J., S. Dudu, T. Rafi and W. Shuly, 2004. Morphological analysis of the Qur'an. Lit. Linguist. Comput., 19(4): 431-452.
    CrossRef    
11. Dukes, K. and N. Habash, 2010. Morphological annotation of Quranic arabic. Proceeding of the Language Resources and Evaluation Conference (LREC), Valletta, Malta.
    
12. Howley, I., E. Mayfield and C.P. Rosé, 2013. Linguistic Analysis Methods for Studying Small Groups. In: Hmelo-Silver, C., A. O'Donnell, C. Chan and C. Chin (Eds.), International Handbook of Collaborative Learning. Taylor and Francis Inc, NY, pp: 184-202.
    
13. Kassim, J.M. and M. Rahmany, 2009. Introduction to semantic search engine. Proceeding of the International Conference on Electrical Engineering and Informatics, Selangor, Malaysia, pp: 380-386.
    CrossRef    
14. Khan, H., S. Saqlain, M. Shoaib and M. Sher, 2013. Ontology based semantic search in Holy Quran. Int. J. Future Comp. Commun., V2: 229.
    
15. Noordin, M. and R. Othman, 2006. An information retrieval system for Quranic texts: A proposed system design. Proceedings of the 2nd Information and Communication Technologies (ICTTA'06), Damascus, 1: 1704-1709.
    CrossRef    
16. Nassourou, M., 2011. Assisting Analysis and Understanding of Quran Search Results with Interactive Scatter Plots and Tables. Retrieved from: http://opus.bibliothek.uni-wuerzburg.de/volltexte/2011/5584/.
    Direct Link
17. Nassourou, M., 2012. Using machine learning algorithms for categorizing Quranic chapters by major phases of Prophet Mohammad's messengership. Int. J. Info. Commun. Technol. Res., 2(11): 863-871.
    
18. Qurat, A. and B. Amna, 2011. Ontology driven information extraction from the Holy Qur'an related documents. Proceedings of the 26th IEEEP Students' Seminar of Pakistan Navy Engineering College National University of Sciences and Technology, Pakistan.
    
19. Saad, S. and N. Salim, 2008. Methodology of ontology extraction for islamic knowledge text. Postgraduate Annual Research Seminar. Retrieved from: http://comp.utm.my/pars/files/2013/04/Methodology-of-Ontology-Extraction-for-Islamic-Knowledge-Text.pdf.
    
20. Saad, S., N. Salim and H. Zainal, 2009. Pattern extraction for Islamic. Proceeding of the International Conference on Electrical Engineering and Informatics, Selangor, Malaysia.
    
21. Shahzadi, N. and A. Shaheen, 2011. Semantic network based semantic search of religious repository. Int. J. Comput. Appl., 36(9): 975-8887.
    
22. Sharaf, A. and E. Atwell, 2009. Knowledge representation of the Quran through frame semantics: A corpus-based approach. Proceedings of the 5th Corpus Linguistics Conference, University of Liverpool, pp: 12.
    
23. Sharaf, A.M. and E.S. Atwell, 2011. QurAna: Corpus of the Quran annotated with pronominal anaphora. Proceedings of the 8ht International Conference on Language Resources and Evaluation (LREC'12), European Language Resources Association (ELRA).
    
24. Sharaf, A.M. and E.S. Atwell, 2012. QurSim: A corpus for evaluation of relatedness in short texts. Proceedings of the 8ht International Conference on Language Resources and Evaluation (LREC'12), European Language Resources Association (ELRA).
    
25. Sherif, M.A. and A.N. Ngomo, 2013. Semantic Quran: A multilingual resource for natural-language processing. Semantic Web J., 6(4): 339-345.
    CrossRef    
26. Zaki, M.J. and W. Meira Jr., 2014. Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press, Cambridge, pp: 12.
    
27. Zameer, A.A. and A.S. Abdul, 2013. A programming approach for the digital Quran applications. Int. J. Eng. Comput. Sci., 13(5).
    

Competing interests

The authors have no competing interests.

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