Deriving item features relevance from collaborative domain knowledge

Maurizio Ferrari Dacrema, Alberto Gasparin, Paolo Cremonesi

An Item based recommender system works by computing a similarity between items, which can exploit past user interactions (collaborative filtering) or item features (content based f…