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@article{172174,
        author = {Penukulapati Durga Maruthi Vara Prasad and Allen Saji and Faizan Niyazuddin and Syed Yusuf Husian and Naymaan Khan and Swati Sharma},
        title = {A Collaborative Filtering Recommendation System for Elective Courses Using Cosine Similarity},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {2120-2124},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172174},
        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.},
        keywords = {Cosine Similarity, Collaborative Filtering, Recommendation System, Streamlit Dashboard},
        month = {January},
        }