content-based filtering

Content-based filtering is a recommendation method that suggests items similar to ones a user has liked before. It analyzes the features of items, such as genres, keywords, or attributes, and matches these characteristics to the user’s preferences. For example, if someone listens to jazz music, the system will recommend other jazz tracks because they share similar qualities. This approach relies on understanding the content of items and individual user tastes, providing personalized recommendations without needing to compare users’ preferences directly.