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Reseach Article

Syntatic Feature based Classification Algorithm to Detect Validity of Text

by Manika Gupta, Vineet Khanna
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 1
Year of Publication: 2017
Authors: Manika Gupta, Vineet Khanna
10.5120/ijca2017911900

Manika Gupta, Vineet Khanna . Syntatic Feature based Classification Algorithm to Detect Validity of Text. International Journal of Computer Applications. 163, 1 ( Apr 2017), 1-4. DOI=10.5120/ijca2017911900

@article{ 10.5120/ijca2017911900,
author = { Manika Gupta, Vineet Khanna },
title = { Syntatic Feature based Classification Algorithm to Detect Validity of Text },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 1 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number1/27356-2017911900/ },
doi = { 10.5120/ijca2017911900 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:08:56.014884+05:30
%A Manika Gupta
%A Vineet Khanna
%T Syntatic Feature based Classification Algorithm to Detect Validity of Text
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 1
%P 1-4
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The complexity of a natural language itself is very challenging as the natural language is not free from ambiguity problem. It is almost impossible to identify that the given text is having sense or not. In today's scenario it becomes even much important to detect that input is given by human or a machine. A valid input with sense is needed everywhere from Social media platforms to Business Intelligence. This Classification algorithm aims to detect whether the given input text is valid, or randomly typed in a keyboard. It returns a percentage value where a lower one means valid text, and a higher value means random text. The approach is based on identifying that the amount of unique chars, amount of vowels of letters, the word/char ratio (in %) are in a usual range. Then it further calculates "deviation score" to compute the accuracy of given input.

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Index Terms

Computer Science
Information Sciences

Keywords

Data mining text mining text classification sentence validation pattern learning