Age Based Hybrid Recommendation System using Machine Learning
Andhoju Karthikeya, Alle Aniesh Kumar, Chennuri Manicharan, Shanmugasundaram Hariharan, Vinay Kukreja, Andraju Bhanu Prasad · 2023
The recommendation system is one of the bigger developments brought about by machine learning in the machine-human interactions. In practically every area, including entertainment, e-commerce, farming, health, etc., recommendation systems are the primary players in delivering greater personalization. When it comes to content-based recommendation systems, there are many social platforms which uses recommendation system for providing improved personalization to their users and to access these social platforms the user need to have an account in that particular social platform. These platforms have different categories of content where not everyone is eligible to a particular content category. There are scenarios where different users may use the same account to access an entertainment application, or if a user inadvertently watched some inappropriate content, the recommendation system will make inappropriate recommendations, which can have an impact on the user's mental health-children. Therefore, after conducting research on the problem statement and reviewing various existing research works, machine learning model is proposed that offers recommendations to the user after determining the user's age and gender in order to deliver appropriate recommendations to the users.