ELECTIVE RECOMMENDATION SYSTEM (KEY IJP************521)

• G . Manoj,Golla Meghana ,Munagala Naga Sameera ,Ayush Chhetri

Abstract

The paper project discussed herein targets, in higher detail, the development of an elective recommendation system with the use of techniques related to machine learning and NLP. It will recommend courses based on textual course descriptions and user inputs relevant to the academic goal and preference of the learner. Recommendations would be done in consideration of a textual course description and the user input towards academic goal alignment and learnerspreferences. To meet this objective, many strategies have been taken on board that entails: Content-Based Filtering, Collaborative Filtering, Semantic Analysis using SBERT. Results in detail would then be judged against different metrics, like Precision @K, Recall @K, and F1 Score. Of course, all the results undoubtedly show the superiority of SBERT; hence, it provides flexibility and scalability for any modern educational environment.