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E-mail is a widely used communication medium in today’s digital world, but it lacks a reliable way to confirm whether a message has been delivered or read. This creates uncertainty for users, especially in important communications. To address this limitation, a system is proposed that provides a message tracking feature, allowing senders to know the status of their e-mails, such as delivery and opening. This enhances trust and effectiveness in communication. At the same time, Online Social Networks (OSNs) face issues related to unwanted or inappropriate content appearing on users’ personal spaces. Current platforms offer limited control over such posts. To solve this problem, a system is introduced that enables users to manage and filter messages on their walls using customizable rules. These rules allow users to define what type of content is acceptable. In addition, a Machine Learning-based classifier is used to automatically analyze and categorize messages, supporting intelligent filtering. This approach improves content control, user privacy, and overall experience in both e-mail communication and social networking platforms. Keywords— E-mail Tracking ; Message Receipt System ; Online Social Networks(OSNs) ; Content Filtering ; Machine Learning Classifier.
Published in: International Journal of Creative and Open Research in Engineering and Management
Volume 02, Issue 03, pp. 1-6