INTELLIGENT COLLEGE ENQUIRY CHATBOT USING NLP FOR ENHANCED STUDENT INTERACTION

This project aims to develop a College Enquiry Chatbot that leverages Natural Language Processing (NLP) techniques to address queries posted by students, such as college details, course-related questions, location, fee structure, and more. The chatbot is a web application designed to analyze and comprehend user messages using machine learning algorithms integrated with NLP for enhanced query understanding and response accuracy. Users can interact with the system by simply typing their queries into the chatbot, which provides precise and contextually relevant answers. The chatbot eliminates the need for students to visit the college in person for inquiries. Additionally, users can provide feedback or suggestions through a dedicated suggestion box. The system features an engaging Graphical User Interface (GUI), simulating an interaction akin to conversing with a real person. The project employs HTML, CSS, and JavaScript for the frontend and Python for the backend, with NLP models enabling robust question analysis and response generation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-22
DOI
https://doi.org/10.5281/zenodo.14204415
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

INTELLIGENT COLLEGE ENQUIRY CHATBOT USING NLP FOR ENHANCED STUDENT INTERACTION

Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

INTELLIGENT COLLEGE ENQUIRY CHATBOT USING NLP FOR ENHANCED STUDENT INTERACTION

article en

Abstract

This project aims to develop a College Enquiry Chatbot that leverages Natural Language Processing (NLP) techniques to address queries posted by students, such as college details, course-related questions, location, fee structure, and more. The chatbot is a web application designed to analyze and comprehend user messages using machine learning algorithms integrated with NLP for enhanced query understanding and response accuracy. Users can interact with the system by simply typing their queries into the chatbot, which provides precise and contextually relevant answers. The chatbot eliminates the need for students to visit the college in person for inquiries. Additionally, users can provide feedback or suggestions through a dedicated suggestion box. The system features an engaging Graphical User Interface (GUI), simulating an interaction akin to conversing with a real person. The project employs HTML, CSS, and JavaScript for the frontend and Python for the backend, with NLP models enabling robust question analysis and response generation.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 57%
AI in Service Interactions
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