Leveraging Aggregate Ratings for Improving Predictive Performance of Recommender Systems

39 Pages Posted: 8 Jun 2009

See all articles by Akhmed Umyarov

Akhmed Umyarov

New York University (NYU) - Leonard N. Stern School of Business

Alexander Tuzhilin

New York University (NYU) - Leonard N. Stern School of Business; New York University (NYU) - Department of Information, Operations, and Management Sciences

Date Written: May 2009

Abstract

This paper describes an approach for incorporating externally specified aggregate ratings informationinto certain types of recommender systems, including two types of collaborating filteringand a hierarchical linear regression model. First, we present a framework for incorporating aggregaterating information and apply this framework to the aforementioned individual rating models.Then we formally show that this additional aggregate rating information provides more accuraterecommendations of individual items to individual users. Further, we experimentally confirm thistheoretical finding by demonstrating on several datasets that the aggregate rating informationindeed leads to better predictions of unknown ratings. We also propose scalable methods forincorporating this aggregate information and test our approaches on large datasets. Finally, wedemonstrate that the aggregate rating information can also be used as a solution to the cold startproblem of recommender systems.

Keywords: Recommender systems, collaborative filtering, hierarchical linear models, predictive models, aggregate ratings, cold-stat problem

Suggested Citation

Umyarov, Akhmed and Tuzhilin, Alexander, Leveraging Aggregate Ratings for Improving Predictive Performance of Recommender Systems (May 2009). NYU, Stern School of Business, Center for Digital Economy Research, Vol. , pp. -, 2009. Available at SSRN: https://ssrn.com/abstract=1415227

Akhmed Umyarov (Contact Author)

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Alexander Tuzhilin

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

New York University (NYU) - Department of Information, Operations, and Management Sciences

44 West Fourth Street
New York, NY 10012
United States

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