SMS Spam Filtering based on Text Classification and Expert System

被引：0

作者：

Bozan, Yavuz Selim ^{[1
]}

Coban, Onder ^{[1
]}

Ozyer, Gulsah Tumuklu ^{[1
]}

Ozyer, Baris ^{[1
]}

机构：

[1] Ataturk Univ, Bilgisayar Muhendisligi Bolumu, Erzurum, Turkey

来源：

2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年

关键词：

Spam SMS; Bayes; SVM; k-NN; expert systems; mobile system software; android;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Even though short message service(SMS) is gradually being replaced by social network sites' messaging systems, it still is one of the most widely used communication systems. For reasons such as well established e-mail filter systems, cheap SMS bundles and ineffective spam solutions for message services, SMS is one of the services which is widely used by advertising companies. In this study, expert system and data classification methods are proposed for SMS spam problem and a prototype software for Jelly Bean version of Android operating system. SVM, bayesian classification and k-NN classification methods applied and 98.61%, 97.55% and 93.35% successful results were obtained.

引用

页码：2345 / 2348

页数：4

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