Latent factor models with additive and hierarchically-smoothed user preferences
WSDM, 2013.
EI
Abstract:
Items in recommender systems are usually associated with annotated attributes: for e.g., brand and price for products; agency for news articles, etc. Such attributes are highly informative and must be exploited for accurate recommendation. While learning a user preference model over these attributes can result in an interpretable recommen...More
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