AI engineering glossary · Time series recsys
What is user-based collaborative filtering?
User-based collaborative filtering (also called User-user CF): A method that finds users most similar to the target user and predicts ratings as a similarity-weighted average of those neighbours' ratings. It is intuitive but costly with very many users, and similarity changes as behaviour changes.
User-based collaborative filtering: an example
Find the 30 users whose past ratings correlate most with yours and average their ratings for a film you have not seen.
Related terms
More Time series recsys terms
- User-item matrix
- Vector autoregression
- Volatility clustering
- Weak stationarity
- Weighted absolute percentage error
- White noise
- Wide and Deep
- Additive decomposition
Where you learn it
User-based collaborative filtering is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.