Abstract

Abstract: The recommendation system has become a necessity in the modern world. This recommendation system encompasses a wide range of industries, including education, entertainment, health, business, and so on. The University recommendation system is a system that makes suggestions, and students are assigned to the appropriate university based on their scores. Students frequently come to a halt as a result of the rapid growth of data volume and a lack of educational knowledge and choose incorrect universities as a result of it. As a result, there is a need for a recommendation system that can understand user needs and recommend suitable universities. In this paper, we present an undergraduate and graduate university recommendation system that can assist students in selecting the best graduate university or undergraduate university for their academic profile. Here, we used a variety of data-mining techniques to transform the student database into a universal database format by using academic data from successful students who were able to study abroad. Following that, we created a machine learning algorithm capable of calculating the similarity between training and learning. Test results are based on weighted scores. We computed the N similar users for the test users using the K nearest neighbour algorithm and the weighted functions algorithm, and we recommend the top K universities to users based on the N similar users.Keywords: KNN, Feature Weighted, Recommendation System.