Context Window

Content-Based Filtering is a machine learning technique that recommends items to users based on the attributes of items they have previously shown interest in. It analyzes features such as genre, description, or other characteristics to identify similar items, enabling personalized suggestions that align with individual preferences without relying on other users' behaviors.