An Enhanced Approach Using Collaborative Filtering For Generating Under Graduate Program Recommendations

V. Vaidhehi, R Suchithra · 2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP) · 2019

The Students of class 12 in India choose a program from a pool of programs offered by higher education institutions. It is proven that students end up choosing inappropriate programs as they lack proper guidance in program selection. As there are multiple program options for students after class 12, this research work is towards the recommendation of appropriate programs for the students by using collaborative filtering algorithms. This research work creates an implicit rating matrix using the academic information of the students. The implicit rating matrix is created by using the domain knowledge of the application. Augmenting the domain knowledge with different types of collaborative filtering like user-based and item-based using implicit rating matrix shows an improvement in the performance of the recommender systems.

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