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Reseach Article

Improving Accuracy of Text Classification for SMS Data

by Hiral D. Padhiyar, Dilipsinh N. Padhiar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 169 - Number 1
Year of Publication: 2017
Authors: Hiral D. Padhiyar, Dilipsinh N. Padhiar
10.5120/ijca2017914429

Hiral D. Padhiyar, Dilipsinh N. Padhiar . Improving Accuracy of Text Classification for SMS Data. International Journal of Computer Applications. 169, 1 ( Jul 2017), 19-21. DOI=10.5120/ijca2017914429

@article{ 10.5120/ijca2017914429,
author = { Hiral D. Padhiyar, Dilipsinh N. Padhiar },
title = { Improving Accuracy of Text Classification for SMS Data },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 169 },
number = { 1 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 19-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume169/number1/27949-2017914429/ },
doi = { 10.5120/ijca2017914429 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:16:11.288985+05:30
%A Hiral D. Padhiyar
%A Dilipsinh N. Padhiar
%T Improving Accuracy of Text Classification for SMS Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 169
%N 1
%P 19-21
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text classification has become one of the major techniques for organizing and managing online information; similarly SMS classification is also an important task now a day. In this paper, we have focused on the issue of short words used in SMS (hpy for happy, bday for birthday) which reduces classification accuracy, so after removing such words with original words, we got better accuracy. We used Decision tree Algorithm for classification of SMS data as it is giving better accuracy then other classifiers. But still replacing all possible short words for the given word dynamically by the original word is an issue.

References
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  2. M.Sukanya, S. (2012). Techniques on Text Mining. ICACCCT.
  3. Mita K. Dalal, M. A. (2011). Automatic Text Classification: A Technical Review. International Journal of Computer Applications .
  4. QASEM A. AL-RADAIDEH, E. M.-S. (2011). An Approach for Arabic Text Categorization Using Association Rule Mining. International Journal of Computer Processing Of Languages.
  5. Yun Yang, Y. W. (2010). The Improved Features Selection for Text Classification. 2nd International Conference on Computer Engineering and Technology. IEEE.
Index Terms

Computer Science
Information Sciences

Keywords

Decision Tree Text Classification