Interesting study that will help better define the text genre. Applicable to databases is a great feature that will help classify different data. Since I'm currently performing assignment on statistics related to the ungrouped frequency distribution (like in this example https://assignment.essayshark.com/blog/example-of-ungrouped-frequency-distribution-table/), this method could be included in the work.
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%0 Journal Article
%1 lim2005automatic
%A Lim, C.
%A Lee, K.
%A Kim, G.
%D 2005
%I Springer
%J Natural Language Processing, Springer, Berlin
%K
%T Automatic genre detection of web documents
@article{lim2005automatic,
added-at = {2018-11-19T17:46:00.000+0100},
author = {Lim, C. and Lee, K. and Kim, G.},
biburl = {https://www.bibsonomy.org/bibtex/27873b6a3983d09d4940bdb48482077c3/benjerie},
interhash = {81a5456d12dd10e3f59cebb1585ef20d},
intrahash = {7873b6a3983d09d4940bdb48482077c3},
journal = {Natural Language Processing, Springer, Berlin},
keywords = {},
publisher = {Springer},
timestamp = {2018-11-19T17:46:00.000+0100},
title = {{Automatic genre detection of web documents}},
year = 2005
}