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Machine Learning Based Approaches for Recommending Colleges to HSC Appointees

Corresponding Author : M. Rahman (moqsad-cse@sust.edu)

Authors : M.Rahman (moqsad-cse@sust.edu)

Keywords : Recommender System, K nearest neighbor, Memory-based approach, Model-based approach, College Recommendation

Abstract :

Getting admitted to a suitable college that provides quality higher education becomes the dream of every student after crossing the barrier of the Secondary School Certificate (SSC) exam. Insufficiency of proper quality institutions and the high increasing rate of candidates are the main challenges against the attainment of this dream. Mitigation of this challenge may be possible through a recommender system. Is there any possibility of a recommender system that will recommend suitable colleges to a higher secondary education appointee? What are the main factors for evaluating an institution as appropriate for a candidate? This work is dedicated to building such a recommender system. Some important factors are extracted from a database containing information about the results of secondary and Higher Secondary Certificate (HSC) exams of Bangladesh. A bunch of machine learning-based approaches categorized as memory-based and model-based collaborative filtering schemes are implemented for building the system. All the approaches are implemented following two root concepts: rating-based and person-based approaches. Discreet analysis and comparison among approaches are presented in the end.

Published on March 7th, 2021 in Volume 2 Issue 1 & 2, Computer Science, Electrical and Electronics