A Content-based Hostel and Mess Recommendation System for Educational Institutions

Authors: Pravin R. Pachorkar, Megha M. Tajane, Chaitanya B. Pawar, Gaurav S. Pawar, Rupesh B. Patil

Country: India

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Abstract: In today's rapidly evolving educational landscape, the well-being and satisfaction of students are paramount. One critical aspect of student life is finding suitable hostel accommodations and mess facilities. This research paper introduces a novel approach to address this challenge through the development of a content-based hostel and mess recommendation system. Leveraging advanced data analytics, machine learning techniques, and user profiling, this system aims to provide personalized, data-driven recommendations to students based on their unique preferences and requirements. The proposed content-based recommendation algorithm analyses rich datasets encompassing textual descriptions, amenities, location, pricing, meal options, dietary preferences, and user feedback. It then calculates relevance scores for hostels and mess facilities, offering tailored suggestions that enhance the overall student experience. The system also incorporates mechanisms for continuous learning and feedback integration to refine recommendations over time. Ultimately, this research contributes to the broader discourse on the intersection of technology, education, and student satisfaction. By enhancing the hostel and mess selection process, educational institutions can significantly improve student wellbeing, retention rates, and overall academic success.

Keywords: Content-based Filtering, Educational Technology, Hostel Recommendation, Mess Recommendation, Machine Learning, Student Satisfaction

Paper Id: 230538

Published On: 2024-03-31

Published In: Volume 12, Issue 2, March-April 2024

Cite This: A Content-based Hostel and Mess Recommendation System for Educational Institutions - Pravin R. Pachorkar, Megha M. Tajane, Chaitanya B. Pawar, Gaurav S. Pawar, Rupesh B. Patil - IJIRMPS Volume 12, Issue 2, March-April 2024.

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