Hybrid Recommender System of university programs for high school students using Deep Learning
Sistema de recomendación de programas universitarios para estudiantes de educación media basado en Deep Learning
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High school students who are faced with the selection of academic programs decide based on program information available in search engines, websites, vocational counselling by advisors, or tests. However, these alternatives have limitations because they do not take into important historical and sociodemographic information, or in case of the advisors, they cannot guide all students. This work supports the decision-making of students through a Recommendation System that presents recommendations based on sociodemographic variables and historical academic data. Also, we propose and compare two methods: a classic Collaborative Filtering model and a Deep Learning model.
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