SUPERVISED LEARNING FOR SPAM DETECTION: A ROBUST AND EFFECTIVE METHODOLOGY
S VIJAY KUMAR, NISHRA MAHVEEN · International journal of engineering science and advanced technology. · 2024
Short Message Service, or SMS, has become less relevant in this day of widely used instant messaging apps. Instead, service providers, companies, and other organisations have come to rely on this service to target regular users for spam and marketing purposes. The usage of regional language material written in English is a new trend in spam communications, which makes it more difficult to identify and filter such messages. This study uses an expanded version of a conventional SMS corpus that includes labelled text messages printed in English that are written in regional languages like Bengali or Hindi, as well as non-spam communications. The labelled text messages were obtained from local mobile users. Using a collection of characteristics and machine learning algorithms that are often used by academics, the Monte Carlo technique is used for learning and classification in a supervised manner. The results show how various algorithms perform in successfully tackling the given task.