AI-Driven Student Networking Portal
In today's constantly changing academic environment, connecting students with career-ready skills, knowledge, and support that they'll need to thrive is more important than ever. That's where Campus Core can help: Campus Core is a smart AI based networking platform designed to connect students in ways that feel natural, useful, and personal. Created for the purpose of bridge the gap between professional networking, academic collaboration, and career development, Campus Core utilizes state of the art AI tools like Market Basket Analysis, Collaborative Filtering, and Content-Based Filtering to match students to the skills, interests, and potential career path they're interested in. Despite being relatively technical, the platform is quite solid and accessible. The frontend is written in HTML, CSS and JavaScript to give it a clean look and feel, but it's built in Python and Flask, who handle everything from the site's login security to a chatbot that answers the user queries. NLP and TF-IDF is used for the search which makes finding the right connections faster and more accurate. And the chatbot that uses Mistral API is always on hand to give real-time career advice or academic support. MongoDB's storage guarantees the system can withstand substantial growth as well. One of the platform's unique features is the Post Section, where students can post job openings, internships, academic events and more-create a space to really feel connected to the college experience. With AI-driven recommendations, real-time search and interactive tools build in, Campus Core solves the common student problems of missed opportunities and fragmented communication: A platform where real people can connect and actually learn, find new roads and build meaningful connections that will help them thrive beyond graduation.
Authors
- T A MohanaPrakash
- P V Lathashree
- A Divyashree
- Roshni Reju
- V Sonika
- H Nandagopal
Institutions
- CMR University (IN)
Publication Details
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1109/icict64420.2025.11005165
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00