What is normalization in recommendation systems?
Updated May 16, 2026
Short answer
Normalization adjusts rating scales to remove user bias.
Deep explanation
Users rate differently; some are generous while others are strict. Normalization adjusts ratings by subtracting user mean or scaling values to make comparisons fair.
Real-world example
Adjusting movie ratings across different users.
Common mistakes
- Ignoring user bias in ratings.
Follow-up questions
- What is z-score normalization?
- Why normalize?