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University Recommender System based on Student Profile using Feature Weighted Algorithm and KNN | IEEE Conference Publication | IEEE Xplore

University Recommender System based on Student Profile using Feature Weighted Algorithm and KNN


Abstract:

This article removes the recommender structure for undergrad and graduate understudies which can help with picking the best schools matching their profile. The proposed m...Show More

Abstract:

This article removes the recommender structure for undergrad and graduate understudies which can help with picking the best schools matching their profile. The proposed model has used different extracting techniques for scrapping the data based on student profiles who have secured the seat successfully earlier. Then, machine learning technology is used to calculate the weighted scores based upon the training and testing data. This research study has introduced the KNN and Feature weighted algorithms to display the top N comparable clients for the test clients and recommend the Top M colleges to clients from the N comparative clients. As there is a colossal course of action of data and User profile, this research work is highly intended to use Knowledge-based techniques for two unmistakable models. Case-based information recommendation is used to calculate Graduate recommendations and constant-based recommendation is used for Undergraduate proposals.
Date of Conference: 07-09 April 2022
Date Added to IEEE Xplore: 27 April 2022
ISBN Information:
Conference Location: Erode, India
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I. Introduction

Understudies who need to want their higher examinations to apply for various colleges with their scholarly profile past state-sanctioned [13] test scores like GRE, TOEFL, IELTS, and SAT. However, all through the interaction, college Choice is the main advance in applying for a degree Entrance. Information acquired from the data set Successful candidates will be to the point of observing their responses Questions, for example, what elements decide financing open doors.[14] For candidates to explicit doctoral level colleges? What class of understudies is normally completely subsidized by MSc software engineers? Or on the other hand, seek after a Ph.D. School? For a confident student for an understudy who prerequisites to apply for higher appraisals in different nations, the school assurance process is troublesome [8]. A part of various rules that need to consider during the application process depending on the person's necessity. This issue can be tended to by demonstrating a recommender framework dependent on different grouping calculations [9]. In this task depending on the Graduate and Undergraduate student dataset and client profile, an overview of the best universities will be prescribed so much that it extends the chances of a student getting entry into those schools [10]. Finally, our recommender system recommends a list University to users who propose to apply for higher studies Facilitates the admission of knowledgeable students who are eager and trying to further their studies based upon financial support [11], [12].

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