DocumentCode :
2570881
Title :
Datamining and Islamic knowledge extraction: alhadith as a knowledge resource
Author :
Aldhlan, K.A. ; Zeki, Akram M.
Author_Institution :
Fac. of Inf. & Commun. Technol., Int. Islamic Univ. Malaysia, Kuala Lumpur, Malaysia
fYear :
2010
fDate :
13-14 Dec. 2010
Abstract :
Qur´an, AL-Sunnah and Islamic traditional books are the rich resources for Muslims that used as the sole authoritative source of knowledge, wisdom and law. The challenge for computer scientists is to extract and represent these knowledge, wisdom and law in computer systems, this knowledge is directed or underlying, therefore, to build an intelligent systems which can answer any question with knowledge from Quran, Al-Sunnah and other Islamic books, special techniques for mining data must be used to deal with this issue, which can help society, both Muslim and non-Muslim, to understand and appreciate the Islamic religion, this paper attempts to understand how the new techniques in data mining can extract Islamic knowledge from its resources, and represent these knowledge in meaningful for the user. Moreover, this study concentrates on Hadith as knowledge resource, and proposes approach to classify Hadith to its categories using supervised learning classification. The finding of this study shows that there are several ways to extract knowledge from Hadith depending on the goal of the knowledge.
Keywords :
authorisation; data mining; ethical aspects; learning (artificial intelligence); social sciences computing; AL-Sunnah; Alhadith; Islamic knowledge extraction; Islamic religion; Islamic traditional book; Qur´an; authoritative source; computer system; data mining; intelligent system; knowledge resource; supervised learning classification; Accuracy; Argon; Context; Data mining; Islamic knowledge; intelligent system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology for the Muslim World (ICT4M), 2010 International Conference on
Conference_Location :
Jakarta
Print_ISBN :
978-1-4244-7920-7
Electronic_ISBN :
978-1-4244-7922-1
Type :
conf
DOI :
10.1109/ICT4M.2010.5971934
Filename :
5971934
Link To Document :
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