SMS Spam Classification Using Machine Learning

Download or read book SMS Spam Classification Using Machine Learning written by Mandar Shivaji Hanchate and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent times, Email and text messages are widely used to communicate as the number of cell phones/mobiles has increased drastically. Short Message Service (SMS) is one of the best and fast ways to communicate. SMSs are used and sent globally for personal and business purposes. But along with important SMSs, we receive other unimportant and fraudulent SMSs too, which is very inconvenient to the users. A lot of bogus messages are being sent for both personal and professional reasons, which is contributing to the problem of SMS spam. Accurately identifying spam SMS is a difficult and important endeavor and the detection of spam is seen as a serious issue in text analysis. The objective of this research is to build a model utilizing machine learning and deep learning principles so that we can understand the semantics of text and then categorize the SMSs as precisely as possible in the spam or non-spam/ham/legitimate classes. Here we used a pre-trained BERT model and collaborated it with several machine learning and deep learning model, among these models, BERT+SVC and BERT+BiLSTM performed the best with 99.10% and 99.19% accuracy respectively on the test dataset.