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@article{180647,
        author = {Jayraj Gajul and Shyam.R.Bramhankar and Sanchit.S.Garad and Vedika.D.Deshmukh and A.D.Tawlare},
        title = {A College Inquiry Chatbot System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1838-1842},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180647},
        abstract = {In today’s digital era, educational institutions are embracing AI-driven technologies to improve communication and streamline administrative processes This paper presents the College Inquiry Chatbot System, an intelligent, cross-platform virtual assistant designed to handle common student queries related to college activities, admissions, academics, and campus facilities Built using Flutter for the frontend and a Python-based backend integrated with Natural Language Processing (NLP) and an XGBoost-based intent classification model, the chatbot delivers real-time, relevant responses to user inquiries The system reduces manual workload, enhances accessibility, and ensures consistent support for students and visitors This paper details the architecture, implementation, and benefits of deploying such a system in a college environment},
        keywords = {College Chatbot, Natural Language Processing (NLP), Intent Classification, XGBoost, Flutter, Python, Virtual Assistant, Student Query System, AI in Education, Cross-Platform Application},
        month = {June},
        }