AI engineering glossary · Time series recsys
What is content-based filtering?
Content-based filtering: A recommendation approach that suggests items whose own attributes, such as genre, text or image features, match the user's past preferences. It needs no other users' data and handles new items, but tends to recommend more of the same.
Content-based filtering: an example
A user who watched three cricket documentaries is shown other documentaries tagged sports.
Related terms
- Collaborative filtering
- Hybrid recommender
- Cold start
- Item embedding
More Time series recsys terms
- Conversion rate
- Correlogram
- Counterfactual evaluation
- Croston's method
- Cyclical component
- DeepAR
- DeepFM
- Differencing
Where you learn it
Content-based 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.