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dc.contributor.authorFazeli, Soude-
dc.contributor.authorLoni, Babak-
dc.contributor.authorBellogin, Alejandro-
dc.contributor.authorDrachsler, Hendrik-
dc.contributor.authorSloep, Peter-
dc.identifier.citationFazeli, S., Loni, B., Bellogin, A., Drachsler, H., & Sloep, P. B. (2014, 6-10 October). Implicit vs. Explicit Trust in Social Matrix Factorization. In Proceedings of the 8th ACM Conference on Recommender systems (RecSys '14) (pp. 317-320). New York, NY, USA: ACM. [Please see also]-
dc.description.abstractIncorporating social trust in Matrix Factorization (MF) methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics (TM) to compute and predict trust scores between users based on their interactions. In this paper, we first evaluate several TMs to find out which one can best predict trust scores compared to the actual trust scores explicitly expressed by users. And, second, we propose to incorporate these trust scores inferred from the candidate TMs into social matrix factorization (MF). We investigate if incorporating the implicit trust scores in MF can make rating prediction as accurate as the MF on explicit trust scores. The reported results support the idea of employing implicit trust into MF whenever explicit trust is not available, since the performance of both models is similar.en_US
dc.description.sponsorshipNELLL, EU FP7 LACE project, Spanish Ministry of Science and Innovation (TIN2013-47090-C3-2)en_US
dc.subjectrecommender systemen_US
dc.subjectmatrix factorizationen_US
dc.subjectimplicit trusten_US
dc.subjectsocial networken_US
dc.titleImplicit vs. Explicit Trust in Social Matrix Factorizationen_US
dc.typeConference proceedingsen_US
Appears in Collections:1. TELI Publications, books and conference papers

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