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A Collaborative Filtering Recommendation System for Elective Courses Using Cosine Similarity

  • Unique Paper ID: 172174
  • Volume: 11
  • Issue: 8
  • PageNo: 2120-2124
  • Abstract:
  • We have tackle the problem of elective recommendation at Presidency University, where students often struggle to secure their preferred subjects. Additionally, when they do receive their electives, they frequently find themselves separated from their friends, leading to confusion. Many students are arbitrarily assigned to different electives by their Heads of Department (HoD) or the timetable committee in an attempt to achieve a balanced distribution among various discipline electives. This project employs a Cosine similarity collaborative filtering recommendation system algorithm designed to assist students in selecting their discipline and open electives based on their academic performance. Furthermore, we provide an interactive dashboard for students and an administrative dashboard for HoD’s to oversee the recommendations without resorting to arbitrary assignments.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 8
  • PageNo: 2120-2124

A Collaborative Filtering Recommendation System for Elective Courses Using Cosine Similarity

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8.01 (Year 2024)
UGC Approved
Journal no 47859

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