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NLP BASED COMPLAINT TRACKING SYSTEM |
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Author Name Vaanathi S, Harishh A, Swetha M, Gokul M P Abstract The "Tikify" Ticket Management System is an innovative web-based platform designed to streamline the reporting, tracking, and resolution of support tickets within organizational or technical environments. It enables users to submit tickets with detailed descriptions, track resolution progress, and access a centralized repository of ticket records and feedback. The system integrates a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model to automate ticket prioritization, ensuring accurate urgency assessment based on textual analysis, while administrators and technicians receive real-time Web Push Notifications regarding assignments, status updates, and priority changes. With role-based dashboards, real-time analytics, and automated notifications, the platform enhances operational efficiency, technician performance, and user satisfaction. The secure and scalable architecture ensures compliance with organizational data protection standards, safeguarding sensitive ticket information through encryption and role-based access control mechanisms. Additionally, the system provides real-time analytics and reporting, allowing organizations to generate customized reports on ticket resolution trends, technician performance metrics, and priority distribution. These insights support resource allocation, performance evaluation, and process optimization. By leveraging automation, data-driven decision-making, and structured feedback mechanisms, the "Tikify" Ticket Management System revolutionizes how support tickets are managed and resolved, enabling organizations to streamline workflows and foster a culture of efficiency and responsiveness. Key Words: Ticket Management System, Priority Prediction, Web-Based Platform, Real-Time Notifications, Natural Language Processing, Data Analytics, Feedback Mechanisms, Data Protection, Automation, Organizational Efficiency. Published On : 2025-03-19 Article Download : ![]() |