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Principal Component Analysis and Factor Analysis to Analyze the Different Arrangements About the Quran’s Suras

EasyChair Preprint no. 7766

17 pagesDate: April 12, 2022

Abstract

Data mining, statistics and data analysis are popular techniques to study datasets and extract knowledge from them. In this paper, principal component analysis and factor analysis were applied to cluster thirteen different given arrangements about the Suras of the Holly Quran. The results showed that these thirteen arrangements can be categorized in two parts such that the first part includes Blachère, Davood, Grimm, Nöldeke, Bazargan, E'temad-al-Saltane and Muir, and the second part includes Ebn Nadim, Jaber, Ebn Abbas, Hazrat Ali, Khazan and Al-Azhar.

Keyphrases: Computer Science, factor analysis, Principal Component Analysis, Quran, statistics

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:7766,
  author = {Yanwen Wang and Javad Garjami and Milena Tsvetkova and Nguyen Huu Hau and Kim-Hung Pho and Mohammad Reza Mahmoudi},
  title = {Principal Component Analysis and Factor Analysis to Analyze the Different Arrangements About the Quran’s Suras},
  howpublished = {EasyChair Preprint no. 7766},

  year = {EasyChair, 2022}}
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