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Does Trust Matter for User Preferences? A Study on Epinions Ratings

Abstract : Recommender systems have evolved during the last few years into useful online tools for assisting the daily e-commerce activities. The majority of recommender systems predict user preferences relating users with similar taste. Prior research has shown that trust networks improve the performance of recommender systems, predominantly using algorithms devised by individual researchers. In this work, omitting any specific trust inference algorithm, we investigate how useful it might be if explicit trust relationships (expressed by users for others) are used to select the best neighbours (or predictors), for the provision of accurate recommendations. We conducted our experiments using data from, a popular recommender system. Our analysis indicates that trust information can be helpful to provide a slight performance gain in a few cases especially when it comes to the less active users.
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Submitted on : Friday, November 24, 2017 - 3:53:23 PM
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Georgios Pitsilis, Pern Hui Chia. Does Trust Matter for User Preferences? A Study on Epinions Ratings. 4th IFIP WG 11.11 International on Trust Management (TM), Jun 2010, Morioka, Japan. pp.232-247, ⟨10.1007/978-3-642-13446-3_16⟩. ⟨hal-01061330⟩



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