I am Abdul Baqi M. Sharaf. I have a PhD from the Leeds University. My thesis title was: ” Annotation of Conceptual Co-reference and Text Mining the Qur’an“. My supervisor was Eric Atwell.
I am investigating ways that computational power could help mine the Qur’anic text! Text Mine the Quran sounds like a job done by machines. However, the Quran is not meant for machine to understand, it is for mankind to comprehend and implement in their life. Machine can only assist in this human understanding by facilitating search and linking up things together. Thus, you will find me in this blog doing lots of human text mining, rather than machine mining, trying to related contemporary events and practices with the Quran and build up a world view out of that.
Qur’an holds lots of interesting information, facts, correlations, patterns, associations between facts and concepts that are difficult to discover by manual processing. Hence, we try to employ computational techniques from the fields of text mining, machine learning, natural language processing, computational linguistics and stylometrics to reveal some of the hidden trends and make it easy to link the scattered yet related concepts in the Qur’an.
I am interested in carrying on computational research to exploit techniques from computational fields and at the same time respect the guidelines and methodology set by early Qur’anic scholars and in their books of Tafsir like Ibn Jarir at-Tabari, Al-Baghawi and Ibn Kathir.
Visit my Wiki for more on this. During my PhD work, I have developed two data sources:
– Related verses from Ibn Katheer. See this page for details and download options.
– Pronoun Tagging. See this page for details and download options.
“Is Computational Linguistics useful for Quranic Studies?“, presented as Guest Speaker at a workshop on “Plagiarism Detection in Arabic” at King Abdul-Aziz University, Jeddah on 17-March-2015. [slides]
Interview in Arabic in the Al-Watan Newspaper, appeared in the “Jumatuna Annex” on 8-Nov-2013. [al-watan interview]
Sharaf, Abdul-Baquee (2012) “Annotation of Conceptual Co-reference and Text Mining the Qur’an“. PhD Thesis, University of Leeds, 2012. [muhammad12phd]
Sharaf, Abdul-Baquee and Atwell, Eric. (2012) “QurSim: A corpus for evaluation of relatedness in short texts“, LREC 2012. [muhammad et al – 2012b- qurSim]
Sharaf, Abdul-Baquee and Atwell, Eric, (2012) “QurAna: corpus of the Quran annotated with pronominal anaphora“, LREC 2012. [muhammad et al – 2012a QurAna]
Sharaf, Abdul-Baquee; Atwell, Eric (2011)التصنيف الآلي للسور القرآنية “Automatic categorization of the Quranic chapters”. 7th International Computing Conference in Arabic (ICCA11).31th May – 2nd June 2011, Imam Mohammed Ibn Saud University, Riyadh, KSA. IN ARABIC [ICCA2011_proceedings_paper26]
Sharaf, A. et al (2010). “NLP Projects on Arabic and the Quran at Leeds University”. Workshop on enriching Arabic digital contents. Damascus, Syria. [alesco-paper-Sharaf10]
Dukes, K. Sharaf, A and Atwell, E (2010). “Online Visualization of Traditional Quranic Grammar using Dependency Graphs.” Conference on The Foundations of Arab Linguistics – Sibawayhi and the Earliest Arabic Grammatical Theory, Faculty of Asian and Middle Eastern Studies, Cambridge University [qcorpus-fal2010]
Dukes, K., Atwell, E., Sharaf, A. (2010) Syntactic Annotation Guidelines for the Quranic Arabic Dependency Treebank. LREC-2010, Valletta, Malta [qsyntax-lrec2010]
Eric Atwell, Kais Dukes, Abdul-Baquee Sharaf, Nizar Habash, et al.(2010) Understanding the Quran: A new Grand Challenge for Computer Science and Artificial Intelligence. Grand Challenges for Computing Research (2010). British Computer Society Workshop. Edinburgh [UnderstandingTheQuran-Edinburgh-2010]
Sharaf, A. and Atwell, E. (2009) A Corpus-based computational model for knowledge representation of the Qur’an. 5th Corpus Linguistics Conference, Liverpool [sharaf2009-cl2009]
Abdul-Baqi Sharaf (2009) The Qur’an Annotation for Text Mining. PhD 1st Year Transfer Report. Leeds University [firstYearTransferReport]
Here are few applications that you may want to try: