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dc.contributor.authorBhattacharjee, Rajat
dc.contributor.authorGoel, Ashish
dc.contributor.authorKollias, Konstantinos
dc.date.accessioned2016-02-25T12:41:33Z
dc.date.available2016-02-25T12:41:33Z
dc.date.issued2009
dc.identifier.citationBhattacharjee R, Goel A, Kollias K (2009) An incentive-based architecture for social recommendations. Proceedings of the third ACM conference on Recommender systems - RecSys ’09. Available: http://dx.doi.org/10.1145/1639714.1639755.
dc.identifier.doi10.1145/1639714.1639755
dc.identifier.urihttp://hdl.handle.net/10754/597532
dc.description.abstractWe present an incentive-based architecture for providing recommendations in a social network. We maintain a distinct reputation system for each individual and we rely on users to identify appropriate correlations and rate the items using a system-provided recommendation language. The key idea is to design an incentive structure and a ranking system such that any inaccuracy in the recommendations implies the existence of a profitable arbitrage opportunity, hence making the system resistant to malicious spam and presentation bias. We also show that, under mild assumptions, our architecture provides users with incentive to minimize the Kullback-Leibler divergence between the ratings and the actual item qualities, quickly driving the system to an equilibrium state with accurate recommendations. Copyright 2009 ACM.
dc.description.sponsorshipResearch conducted while at Stanford University. Researchsupported by NSF ITR grant 0428868 and NSF award0339262.Department of Management Science and Engineering and(by courtesy) Computer Science, Stanford University. Researchsupported by NSF ITR grant 0428868 and gifts fromGoogle, Microsoft, and Cisco.Department of Management Science and Engineering,Stanford University. Research supported by an A. G. LeventisFoundation Scholarship and the Stanford-KAUST alliancefor excellence in academics.
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectIncentives
dc.subjectInformation aggregation
dc.subjectRecommender systems
dc.titleAn incentive-based architecture for social recommendations
dc.typeConference Paper
dc.identifier.journalProceedings of the third ACM conference on Recommender systems - RecSys '09
dc.contributor.institutionGoogle Inc., Mountain View, United States
dc.contributor.institutionStanford University, Palo Alto, United States


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