Major Challenges of Recommender System and Related Solutions (International Journal of Innovative Research in Computer Science & Technology, 2022)
Recommender system is a very young area  of machine learning & Deep Learning research. The basic  goal of the recommender system is to create a relationship  between items and consumers. The relationship provides  recommendations based on user interest. content-based,  collaborative, demographic, hybrid filtering, knowledge based, utility-based, classification model are well-known  recommender models. The model uses an item's  specifications in content-based filtering to suggest other  objects with similar features. Collaborative filtering takes  into the user's previous activity which means the user has  previously viewed or purchased, as well as ratings  Provided by the user to those items and similar conclusions  reached by other users' item lists. View user profile data  such as age category, gender, education, and living area to  detect commonalities with other profiles.[31] All three  filtering techniques are used in hybrid filtering. In the  process of recommendations, various challenges are faced  by the system. So, this paper lists various solutions by  researchers in recent days.
Keywords: Recommender system; content-based filtering; collaborative filtering; Deep Learning