Taxonomy discovery for personalized recommendation

WSDM, pp. 243-252, 2014.

Cited by: 48|Bibtex|Views158|DOI:https://doi.org/10.1145/2556195.2556236
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

Personalized recommender systems based on latent factor models are widely used to increase sales in e-commerce. Such systems use the past behavior of users to recommend new items that are likely to be of interest to them. However, latent factor model suffer from sparse user-item interaction in online shopping data: for a large portion of ...More

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