Automated SMS Classification and spam analysis
International Research Journal of Modernization in Engineering Technology and Science · 2023
The surge in SMS usage as the primary communication method has resulted in a notable upsurge in the quantity of unwanted messages.To combat this issue, an automatic system has been created to categorize SMS messages into either spam or non-spam groups and analyze the attributes of spam messages.The system extracts pertinent characteristics from SMS messages and constructs machine learning models for message classification.Additionally, the system examines the content of spam messages to identify patterns and trends in spam activities.This abstract provides an overview of current techniques employed in spam SMS detection.It explores and diverse avenue for feature decoction and classification, encompassing rule-based methods, machine learning algorithms, and deep learning models.Furthermore, it discusses the challenges present with developing efficacious spam SMS detection systems, such that the dynamic nature of SMS spam and the requirement for substantial training data.Lastly, notable advancements in this field, including the utilization of neural networks and ensemble methods to enhance performance, are highlighted.