College Lens: Real Students Real Insights
Mr. Shreyash S. Gopale1, Ms. Shraddha D. Deshmukh2, Ms. Muskan V. Tandel3, Mr. Arjun S. Jondhale4, Mr. Sharad M. Rokade5
1,2,3,4 Student, Department of Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India.
5Assistant Professor, Department of Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India.
ABSTRACT
In the modern digital era, students rely heavily on online information before selecting a college. However, most existing platforms allow anyone to post reviews without identity verification, leading to fake feedback and unreliable insights. To overcome this issue, College Lens: Real Students Real Insights introduces a trusted review and recommendation system that ensures only verified students of a particular college can submit reviews. Verification is conducted using the student's First Year (FE) result and fees receipt, validated through OCR-based document analysis on the backend. This approach guarantees authenticity and builds a reliable source of real experiences. The platform also assists new admission seekers by predicting possible colleges where they might secure admission based on past admission trends and student performance data. This prediction system is powered by machine learning algorithms implemented using Scikit-learn, providing a ranked list of probable colleges with corresponding chances of admission. The overall system is developed using a React frontend, a Django backend, and a PostgreSQL database, ensuring scalability, data security, and smooth interaction. By integrating verified reviews, predictive analytics, and multimedia resources such as campus photos and placement records, College Lens provides a comprehensive and transparent ecosystem for students. It empowers new applicants with real insights from genuine students and supports informed decision-making in the college selection process.
Keywords: Verified reviews, College selection, OCR verification, Machine learning prediction, Django backend, Scikit-learn, React frontend, Admission recommendation system.
