Volume 15, Issue 3 (12-2018)                   JSDP 2018, 15(3): 89-100 | Back to browse issues page


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Aslani A, Esmaeili M. Finding Frequent Patterns in Holy Quran UsingText Mining. JSDP. 2018; 15 (3) :89-100
URL: http://jsdp.rcisp.ac.ir/article-1-620-en.html
Abstract:   (793 Views)
Quran’s Text differs from any other texts in terms of its exceptional concepts, ideas and subjects. To recognize the valuable implicit patterns through a vast amount of data has lately captured the attention of so many researchers. Text Mining provides the grounds to extract information from texts and it can help us reach our objective in this regard. In recent years, Text Mining on Quran and extracting implicit knowledge from Quranic words have been the object of researchers’ focus. It is common that in Quranic experts’ arguments, different sides of the discussion present different intellectual, logical and some non-integrated minor evidence in order to prove their own theories. More often than not, every side of these arguments disapproves of the other’s hypothesis and in the end it is impossible for them to reach a state of consensus on the matter, the reason is that, they do not have a common basis for their arguments and they do not make use of scientific, logical methods to strongly support their theories. Therefore, using modern technological trends regarding Quranic arguments could lead to resolving so many of current discrepancies, caused by human errors, which exist among Quranic researchers. It can help providing a common ground for their arguments in order to reach a comprehensive understanding.
The method used in this research implements frequent pattern mining algorithms, singular frequent patterns as well as dual and tripe frequent patterns in order to analyze Quranic text, in addition to this, Association rules have also been evaluated in the research.
Out of 54226 extracted association rules for Quranic words which have been evaluated by the use of criteria such as confidence coefficient, support coefficient, lift criteria as well as Co-efficient criteria. Top 10 rules for each criterion have been analyzed and reviewed throughout the project.
Full-Text [PDF 5112 kb]   (226 Downloads)    
Type of Study: Research | Subject: Paper
Received: 2017/12/14 | Accepted: 2018/07/25 | Published: 2018/12/19 | ePublished: 2018/12/19

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