Latent factor models with additive and hierarchically-smoothed user preferences

WSDM, 2013.

Cited by: 37|Bibtex|Views102|DOI:https://doi.org/10.1145/2433396.2433445
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

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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