Abstract  Textual Case#Based Reasoning (TCBR) is an artificia l intelligence approach to problem solving and learning in which textual expertise is collected in a library o f past cases. One of the critical application domai ns is the Islamic Fatawa (religious verdict) domain, which refers to seeking a legal ruling for religious issues that Muslims all over the globe pose on a daily basis. Official religious organizations like Egypt’s Dar al#Ifta 1 is responsible for receiving and answering people’ s religious inquiries daily. Due to the enormous numb er of inquiries Dar al#Ifta receives every day, it cannot be handled at the same time. This task actually requires a certain sm art system that can help in fulfilling people’s needs for answers. However, applying TCBR in the domain of issuing Fatawa faces several challenges related to the language syntax and semantics. The contribution of this paper is to propose an intelli gent fatwa Questions Answering (QA) system that can overcome the challenges and respond to a user’s inquiry through providing semantically closest inquiries that previously answered. Moreover, the paper shows how the proposed system c an learn when a new inquiry arrives. Finally, results will be discussed.  

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[14] Swaroop S. and Ashok K., Biological Solutions for Engineering Problems: A Study in Cross3 Domain Textual Case3Based Reasoning, in Proceedings of the 21 st International Conference on Case#Based Reasoning Research and Development , NY, USA, pp. 3433357, 2013. Islam Elhalwany received his Bsc degree of computers and information systems from Suez Canal University in 2002. He got Information Systems Diploma from Cairo University in 2010 and now he is preparing his Ms thesis in information systems in Cairo University. In addition, he currently works a s software development manager at Egypt s Dar al3Ifta . Ammar Mohammed received his Bsc degree of computer science from Cairo University in 1999 and his Ms degree of computer science from the same university in 2005. He received his PhD degree of computer science from university of Koblenz3Landau, Germany in 2010; he worked as post3doctoral researc h fellow at the same university. In addition, current ly he is assistant professor at Department Computer Scien ce, Institute of Statistical studies and research, Cair o University. Khaled Wassif is an Assistant Professor in Faculty of Computers and Information, Cairo University. He received his Ms and PhD degrees from Cairo University in the field of artificial intelligence. Main research topics of Wassif include machine learning, data and web mining, case3based reasoning and cloud computing. He has supervised or co3 supervised six students on their PhD dissertations and MS thesis. He has supervised numerous undergraduate research projects. Hesham Hefny received his Bsc, MSc and PhD degrees all in electronics and communication engineering from Cairo University in 1987, 1991, 1998, respectively. Currently, he is a Professor of computer science and the Head of the Department of Computer and Information Sciences at the Institute of Statistical Studies and Researc h3 Cairo University. His research of interest include fuzzy systems, artificial neural networks and granu lar computing.