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@article{191279,
        author = {V. Suriya Pushpa Sundar and S. Shirley},
        title = {SMART COMPLAINT TRACKING SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {5934-5938},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191279},
        abstract = {Efficient complaint management plays a vital role in improving service quality and public satisfaction in modern organizations and smart governance systems. However, traditional complaint handling methods are often manual, time-consuming, and lack transparency, leading to delayed responses and unresolved grievances. To address these challenges, this paper proposes a Smart Complaint Tracking System using Machine Learning techniques. The system automatically analyzes user-submitted complaints using Natural Language Processing and classifies them into appropriate categories with the help of TF-IDF feature extraction and machine learning algorithms such as Logistic Regression, Support Vector Machine, and Random Forest. Experimental results show that the proposed system improves complaint classification accuracy, reduces response time, and enhances transparency in complaint resolution. The system can be effectively deployed in smart cities, government services, and large-scale organizations.},
        keywords = {},
        month = {January},
        }