Recommender Systems Questions
Content-based filtering is a recommender system technique that recommends items to users based on their preferences and characteristics. It analyzes the content or attributes of items, such as text, keywords, or metadata, and matches them with the user's profile or previous interactions. This approach focuses on the similarity between items and user preferences, rather than considering the preferences of other users.