Using Textual Case-based Reasoning in Intelligent Fatawa QA System

Using Textual Case-based Reasoning in Intelligent Fatawa QA System

Islam Elhalwany1, Ammar Mohammed1, Khaled Wassif2, Hesham Hefny1
1Institute of Statistical Studies & Researches, Cairo University, Egypt
2Faculty of Computers and Information, Cairo University, Egypt

Abstract: Textual Case-Based Reasoning (TCBR) is an artificial intelligence approach to problem solving and learning in which textual expertise is collected in a library of past cases. One of the critical application domains 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-Ifta1 is responsible for receiving and answering people's religious inquiries daily. Due to the enormous number of inquiries Dar al-Ifta receives every day, it cannot be handled at the same time. This task actually requires a certain smart 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 intelligent Fatwa Questions Answering 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 can learn when a new inquiry arrives. Finally, results will be discussed.

 Keywords: Case based Reasoning, Textual Case Based Reasoning, Questions Answering Systems, Artificial Intelligence, Information Retrieval, and Knowledge-based Systems.

 Received August 29, 2013; accepted March 10, 2014

 

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