Proposing a New Method to Identify Spams in SMS

In recent years, the Internet has become an integral part of our human lives. With the increasing use of the Internet, the number of email users is increasing day by day. This increasing use of e-mail has created problems caused by unsolicited bulk e-mail messages, commonly referred to as spam. Email has now become one of the best ways to advertise, which is why spam emails are generated. Spam emails are emails that the recipient does not want to receive. Too many identical messages are sent to multiple email recipients. Spam is usually generated as a result of providing our email address on an unauthorized or illegal website. There are many effects of spam. It fills our inbox with tons of useless emails. It slows down our internet speed to a great extent. It steals useful information. Therefore, in this research, we propose a new method to identify spam emails written in Persian language. In this method, we have used a combination of machine learning and deep learning techniques to identify email spam. We used the proposed method using Kaggle online data set. The obtained results showed that the proposed method has a better performance in terms of evaluation criteria (accuracy, accuracy, recall and F-Measure) compared to the methods proposed by other researchers.