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Enhancing the Rate of Accuracy and Precision in Spam Filtering in Farsi SMS

Maryam Poorshahsavari, Omid Pourgalehdari. Published in Pattern Recognition.

Communications on Applied Electronics
Year of Publication: 2015
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Maryam Poorshahsavari, Omid Pourgalehdari
10.5120/cae2015651906

Maryam Poorshahsavari and Omid Pourgalehdari. Article: Enhancing the Rate of Accuracy and Precision in Spam Filtering in Farsi SMS. Communications on Applied Electronics 3(3):25-27, October 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Maryam Poorshahsavari and Omid Pourgalehdari},
	title = {Article: Enhancing the Rate of Accuracy and Precision in Spam Filtering in Farsi SMS},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {3},
	number = {3},
	pages = {25-27},
	month = {October},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

This paper introduces a technique for increasing the rate of accuracy in spam filtering and reducing the false positive (fp) in Farsi SMS. This technique is based on combination of naïve bayes assumption with an introduced formula to increase the filtering accuracy up to 90%. In order to validate introduced formula and to measure the accuracy, the obtained results have been surveyed by precision-Recall techniques.

References

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  8. Narayan, A., & Saxena, P. (2013, November). The curse of 140 characters: evaluating the efficacy of SMS spam detection on android. In Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices (pp. 33-42). ACM.
  9. Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms. John Wiley & Sons.

Keywords

SMS Filtering, Naïve bayes Assumption, Spam SMS, Data Mining, False Positive