Collaborative filtering models for recommendations systems
نویسندگان
چکیده
Modern retailers frequently use recommendation systems to suggest products of interest to a collection of consumers. A closely related task is ratings prediction, in which the system predicts a numerical rating that a user u will assign to a product p. In this paper, we build three ratings prediction models for a dataset of products and users from Amazon.com and Yelp.com. We evaluate the strengths and weaknesses of each model, and discuss their effectiveness in a recommendation system.
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تاریخ انتشار 2011