Research Article
Lexical Analysis of Religious Texts using Text Mining and Machine Learning Tools
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 168 - Issue 8 |
| Published: Jun 2017 |
| Authors: Mayuri Verma |
10.5120/ijca2017914486
|
Mayuri Verma . Lexical Analysis of Religious Texts using Text Mining and Machine Learning Tools. International Journal of Computer Applications. 168, 8 (Jun 2017), 39-45. DOI=10.5120/ijca2017914486
@article{ 10.5120/ijca2017914486,
author = { Mayuri Verma },
title = { Lexical Analysis of Religious Texts using Text Mining and Machine Learning Tools },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 168 },
number = { 8 },
pages = { 39-45 },
doi = { 10.5120/ijca2017914486 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Mayuri Verma
%T Lexical Analysis of Religious Texts using Text Mining and Machine Learning Tools%T
%J International Journal of Computer Applications
%V 168
%N 8
%P 39-45
%R 10.5120/ijca2017914486
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper presents a text mining approach to compare and to explore the similarities and the differences between various religious texts using POS Tagging and Term Document Matrix. Automated text mining and machine learning tools have been used for lexical analysis of the ten world famous religious texts: the Holy Bible, the Dhammapada, the Tao Te Ching, the Bhagwad Gita, the Guru Granth Sahib, the Agama, the Quran, the Rig Veda, the Sarbachan and the Torah. The extracted nouns categories were used as features to explore some interesting relationships between these religions and ideas that have emerged in different religions from different geographic regions.
References
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- SAR BACHANRÁDHÁSOÁMÍ (Poetry) https://www.scribd.com/doc/118290685/Sar-Bachan-Radhasoami-Poetry-Volume-One
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