Overcoming accuracy-diversity tradeoff in recommender systems: A variance-based approach

Gediminas Adomavicius, Young Ok Kwon

Research output: Contribution to conferencePaper

16 Scopus citations

Abstract

Collaborative filtering and, more generally, recommender systems represent an increasingly popular and important set of personalization technologies that help people navigate through the vast amounts of information. The performance of recommender systems can be evaluated along several dimensions, such as the accuracy of recommendations for each user and the diversity of recommendations across different users. Intuitively, there is a tradeoff between accuracy and diversity, because high accuracy may often be obtained by safely recommending to users the most popular ("bestselling") items, which can lead to the reduction in recommendation diversity, i.e., less personalized recommendations. And conversely, higher diversity can be achieved by trying to uncover and recommend highly idiosyncratic/personalized items for each user, which are inherently more difficult to predict and, thus, may lead to a decrease in recommendation accuracy. In our research we explore different ways to overcome this accuracy-diversity tradeoff, and in this paper we discuss a variance-based approach that can improve both the accuracy and diversity of recommendations obtained from a traditional collaborative filtering technique. We provide empirical results based on several real-world movie rating datasets.

Original languageEnglish (US)
Pages151-156
Number of pages6
StatePublished - Jan 1 2008
Event2008 Workshop on Information Technologies and Systems, WITS 2008 - Paris, France
Duration: Dec 13 2008Dec 14 2008

Other

Other2008 Workshop on Information Technologies and Systems, WITS 2008
CountryFrance
CityParis
Period12/13/0812/14/08

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    Adomavicius, G., & Kwon, Y. O. (2008). Overcoming accuracy-diversity tradeoff in recommender systems: A variance-based approach. 151-156. Paper presented at 2008 Workshop on Information Technologies and Systems, WITS 2008, Paris, France.