Abstract
The choice of higher education program plays a major role in shaping up one’s career. Hence, it is worth investing time in gathering the right information to make an informed decision. For this cause, to the extent of our knowledge there are no dedicated tools. Students tend to make decision either based on the peer review without giving much thought on it. The system aims to consider student’s interest as sole parameter to recommend the course which will be best to pursue. The interest of the student will be gauged on subjects which the student has already undertaken as undergraduate courses. The proposed system provides the user with a Web application where the user can make its profile and input his/her interest based on the parameters. K-Nearest Neighbours Classification Algorithm is used to select the best-suited courses based on Euclidean distance. The proposed recommendation system is a content-based Recommendation System since it recommends items (courses in this case) based on content of items (the undergraduate courses) and user profile (the rating of courses based on interest). Our proposed system implements a recommendation prototype with a focus on Computer Science and Information Technology disciplines as the chosen field of knowledge.
Supported by Ramrao Adik Institute of Technology.
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Pal, S., Shahi, A., Rai, S., Gulwani, R. (2021). Course Recommendation System for Post-graduate (Masters in Science) Aspirants. In: Chaki, N., Pejas, J., Devarakonda, N., Rao Kovvur, R.M. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-15-8767-2_31
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DOI: https://doi.org/10.1007/978-981-15-8767-2_31
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