AI engineering glossary · Time series recsys
What is item-based collaborative filtering?
Item-based collaborative filtering (also called Item-item CF): A method that recommends items similar to ones a user already liked, where similarity is measured from co-occurring interactions across all users. Item similarities change slowly, so they can be precomputed, which made it popular in large systems.
Item-based collaborative filtering: an example
People who bought a phone case often bought a screen guard, so the guard is suggested to a phone-case buyer.
Related terms
More Time series recsys terms
- Kalman filter
- KPSS test
- LambdaMART
- Latent factors
- Learning to rank
- Listwise ranking
- Ljung-Box test
- Long tail
Where you learn it
Item-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.