What is feature engineering in recommendation systems?

Feature engineering transforms raw data into meaningful signals for recommendation models.

Feature engineering includes creating user features (recency, frequency, engagement), item features (category, popularity), and contextual features (time, device). It also includes interaction features like user-item affinity scores. Good feature engineering often improves model performance more than algorithm choice.