A Hybrid CNN-LSTM Model for SMS Spam Detection in Arabic and English Messages
نویسندگان
چکیده
منابع مشابه
An Effective Model for SMS Spam Detection Using Content-based Features and Averaged Neural Network
In recent years, there has been considerable interest among people to use short message service (SMS) as one of the essential and straightforward communications services on mobile devices. The increased popularity of this service also increased the number of mobile devices attacks such as SMS spam messages. SMS spam messages constitute a real problem to mobile subscribers; this worries telecomm...
متن کاملFiltering spam e-mail from mixed arabic and english messages: a comparison of machine learning techniques
Spam is one of the main problems in emails communications. As the volume of non-english language spam increases, little work is done in this area. For example, in Arab world users receive spam written mostly in arabic, english or mixed Arabic and english. To filter this kind of messages, this research applied several machine learning techniques. Many researchers have used machine learning techn...
متن کاملSMS 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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Unfortunately, among internet services, users are faced with several unwanted messages that are not even related to their interests and scope, and they contain advertising or even malicious content. Spam email contains a huge collection of infected and malicious advertising emails that harms data destroying and stealing personal information for malicious purposes. In most cases, spam emails con...
متن کاملA Bi-Level Text Classification Approach for SMS Spam Filtering and Identifying Priority Messages
Short Message Service (SMS) traffic is increasing day by day and trillions of sms are sent and received by billions of users every day. Spam messages are also increasing in same proportionate. Numbers of recent advancements are taking place in the field of sms spam detection and filtering. The objective of this work is twofold, first is to identify and classify spam messages from the collection...
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ژورنال
عنوان ژورنال: Future Internet
سال: 2020
ISSN: 1999-5903
DOI: 10.3390/fi12090156