An Automated Recommender System for Educational Institute in India

Garanayak, Mamata and Sahoo, Sipra and Mohanty, Sachi Nandan and Jagadev, Alok Kumar (2020) An Automated Recommender System for Educational Institute in India. EAI Endorsed Transactions on Scalable Information Systems, 7 (26): e9. ISSN 2032-9407

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This study aims to suggest a recommender System for undergraduate students who desire to seek admission into engineering courses in different Indian Institute of Technology (IITs) in India. Initially, the focus is to purpose a recommender system for admission into the top 10 IIT on a pilot basis in four common branches such as Electrical Engineering, Computer Science and Engineering, Mechanical Engineering, Civil Engineering. Data were collected from different authentic sources from 2016 to 2018. A model was built to predict the ranks for 2019 for each branch of every IITs. This paper illustrates prediction using Time Series Forecasting and recommendation algorithm using classification techniques. A comparative study of Random Forest Classification and K-Nearest Neighbor classification has been done. Finally, the recommendation algorithm shown reliable results with high accuracy in prediction model. It can be diversify and implement other streams as part of future work.

Item Type: Article
Uncontrolled Keywords: Recommender system, Random Forest Classification, K-Nearest Neighbor (KNN)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 08 Oct 2020 13:52
Last Modified: 08 Oct 2020 13:52

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