May 2, 2024, 4:43 a.m. | Jibril Frej, Anna Dai, Syrielle Montariol, Antoine Bosselut, Tanja K\"aser

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.10876v2 Announce Type: replace-cross
Abstract: Current course recommender systems primarily leverage learner-course interactions, course content, learner preferences, and supplementary course details like instructor, institution, ratings, and reviews, to make their recommendation. However, these systems often overlook a critical aspect: the evolving skill demand of the job market. This paper focuses on the perspective of academic researchers, working in collaboration with the industry, aiming to develop a course recommender system that incorporates job market skill demands. In light of the job …

abstract arxiv course cs.ir cs.lg current demand however interactions job job market market paper ratings recommendation recommender systems reviews skill systems type

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