College Enquiry Chatbot Project Guide

Handling hundreds of student inquiries manually puts a strain on college administration staff. Questions about admission procedures, course structures, fees, eligibility, and deadlines flood official communication channels every year. Automating these responses using a smart chatbot saves time, ensures faster communication, and enhances student experience. A college enquiry chatbot can be integrated into websites or WhatsApp groups to handle multiple queries simultaneously 24/7.

By using Natural Language Processing (NLP) techniques like intent classification, named entity recognition, and smart response generation, we can build a chatbot capable of answering common student queries. Predefined FAQs, fallback intents for unknown queries, and dynamic database lookups make the chatbot intelligent. Frameworks like Rasa, Dialogflow, or custom-built TensorFlow-based bots can be used to implement the system effectively.

The chatbot receives text input from students, detects intent (e.g., Admission Dates, Fee Structure, Course Details), and responds with predefined answers or database lookups. If an unknown query is detected, it can escalate to human staff or suggest related FAQs. Training the model involves curating intents, creating examples, training classification models, and building conversation flows that guide students accurately to the information they seek.

• Collect common FAQs and categorize them into intents (Admissions, Courses, Facilities, Scholarships, etc.).
• Train an intent classification model using NLP frameworks like Rasa, Dialogflow, or custom TensorFlow pipelines.
• Design conversational flows with fallback intents, form filling for dynamic queries, and response variation strategies.
• Deploy the chatbot on websites, mobile apps, or integrate with messaging apps like WhatsApp and Facebook Messenger.
• Continuously retrain the model based on new student queries to make it smarter over time.

• Rasa Open Source Documentation
• Dialogflow Essentials
• TensorFlow Text Processing