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Feature Selection and Reduction for Persian Text Classification

by Zahra Robati, Morteza Zahedi, Najmeh Fayazi Far
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 17
Year of Publication: 2015
Authors: Zahra Robati, Morteza Zahedi, Najmeh Fayazi Far
10.5120/19414-9005

Zahra Robati, Morteza Zahedi, Najmeh Fayazi Far . Feature Selection and Reduction for Persian Text Classification. International Journal of Computer Applications. 109, 17 ( January 2015), 1-5. DOI=10.5120/19414-9005

@article{ 10.5120/19414-9005,
author = { Zahra Robati, Morteza Zahedi, Najmeh Fayazi Far },
title = { Feature Selection and Reduction for Persian Text Classification },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 17 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number17/19414-9005/ },
doi = { 10.5120/19414-9005 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:01.400634+05:30
%A Zahra Robati
%A Morteza Zahedi
%A Najmeh Fayazi Far
%T Feature Selection and Reduction for Persian Text Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 17
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the rapid growth of the World Wide Web and increasing availability of electronic documents, the automatic text classification became a general and important machine learning problem in text mining domain. In text classification, feature selection is used for reducing the size of feature vector and for improving the performance of classifier. This paper improved Dominance which is a feature selection criterion and proposed Extended Dominance (E-Dominance) as a new criterion. E-Dominance is compared favorably with usual feature selection methods based on document frequency (DF), information gain (IG), Entropy, ?2 and Dominance on a collection of XML documents from Hamshahri2 which is a commonly used in Persian text classification. The comparative study confirms the effectiveness of proposed feature selection criterion derived from the Dominance.

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Index Terms

Computer Science
Information Sciences

Keywords

Text Classification E-Dominance feature selection criterion

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