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

EasyChair Preprint 7766

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, Principal Component Analysis, Quran, factor analysis, statistics

@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 7766},
  year      = {EasyChair, 2022}}