juniorRecommendation Systems
What is content-based recommendation?
Updated May 16, 2026
Short answer
Content-based systems recommend items similar to those a user has liked based on item features.
Deep explanation
It uses features like genre, category, or embeddings to compute similarity between items. User profiles are built from features of previously liked items.
Real-world example
YouTube recommending similar videos based on watched content.
Common mistakes
- Ignoring user diversity leading to filter bubbles.
Follow-up questions
- What features are used?
- What is drawback?