A Model for Filtering Spam SMS Using Deep Machine Learning Technique
نویسندگان
چکیده
منابع مشابه
SMS Spam Detection using Machine Learning Approach
Over recent years, as the popularity of mobile phone devices has increased, Short Message Service (SMS) has grown into a multi-billion dollars industry. At the same time, reduction in the cost of messaging services has resulted in growth in unsolicited commercial advertisements (spams) being sent to mobile phones. In parts of Asia, up to 30% of text messages were spam in 2012. Lack of real data...
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The Short Message Service (SMS) have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Naïve Bayesian algorithm is one of the most effective approaches used in filtering te...
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We investigate how one can use optimization methods to attune spam filters to the specific issues found in the spam filtering area. Among those issues is the need to modelize and manage spammers strategies to delude the filters. To adress this issue, we propose a selective learning scheme designed to maximize learning efficiency. In an offline context, this model uses a simple metaheuristic app...
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The article gives an overview of some of the most popular machine learning methods (Bayesian classification, k-NN, ANNs, SVMs) and of their applicability to the problem of spam-filtering. Brief descriptions of the algorithms are presented, which are meant to be understandable by a reader not familiar with them before. A most trivial sample implementation of the named techniques was made by the ...
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Mobile or SMS spam is a real and growing problem primarily due to the availability of very cheap bulk pre-pay SMS packages and the fact that SMS engenders higher response rates as it is a trusted and personal service. SMS spam filtering is a relatively new task which inherits many issues and solutions from email spam filtering. However it poses its own specific challenges. This paper motivates ...
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ژورنال
عنوان ژورنال: IJARCCE
سال: 2021
ISSN: 2319-5940,2278-1021
DOI: 10.17148/ijarcce.2021.10403