Research Article
A Strategic Approach in Course Recommendation System Using Similarity Models
@INPROCEEDINGS{10.4108/eai.23-2-2024.2346986, author={Angel Susan Vino and Diya AlDin and Parvathy Menon and Sandosh S}, title={A Strategic Approach in Course Recommendation System Using Similarity Models}, proceedings={Proceedings of the International Conference on Advancements in Materials, Design and Manufacturing for Sustainable Development, ICAMDMS 2024, 23-24 February 2024, Coimbatore, Tamil Nadu, India}, publisher={EAI}, proceedings_a={ICAMDMS}, year={2024}, month={6}, keywords={recommendation e-learning content-based nlp similarity}, doi={10.4108/eai.23-2-2024.2346986} }- Angel Susan Vino
Diya AlDin
Parvathy Menon
Sandosh S
Year: 2024
A Strategic Approach in Course Recommendation System Using Similarity Models
ICAMDMS
EAI
DOI: 10.4108/eai.23-2-2024.2346986
Abstract
In response to the changing dynamics of the modern world, where information and education play key roles, recommendation systems have developed as critical components across a wide range of digital platforms. This study digs into the development of an online course selection system geared to fulfill the educational needs of a diverse audience, including working professionals, students, and ardent learners committed to lifelong learning. Against the backdrop of an ever-changing ecosystem, this research project intends to harness recommendation algorithms to greatly improve learning outcomes by providing individualized and adaptable learning opportunities. The prevalence of recommendation systems throughout social media, applications, websites, and numerous technologies emphasizes their importance, driving our initiative to con-tribute to the educational area through the development of a specific online course recommendation system
