Personalization, Algorithms, Recommendation System.
ratings for items they haven’t yet experienced. This scenario is akin to a prelude, where users share their thoughts and expectations before diving into the content. These ratings can be influenced by various factors: word-of-mouth recommendations, promotional materials, or personal inclinations.