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Trust Prediction via Matrix Factorisation

Published:19 September 2019Publication History
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Abstract

In this article, we propose the PTP-MF (Pairwise Trust Prediction through Matrix Factorisation) algorithm, an approach to predicting the intensity of trust and distrust relations in Online Social Networks (OSNs).

Our algorithm maps each OSN user i onto two low-dimensional vectors, namely, the trustor profile (describing her/his inclination to trust others) and the trustee profile (modelling how others perceive i as trustworthy) and it computes the trust a user i places in a user j as the dot product of trustor profile of i and the trustee profile of j. The PTP-MF algorithm incorporates also biases in trustor and trustee behaviour to make more accurate predictions.

Experiments on four real-life datasets indicate that the PTP-MF algorithm significantly outperforms other methods in accuracy and it showcases a high scalability.

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          • Published in

            cover image ACM Transactions on Internet Technology
            ACM Transactions on Internet Technology  Volume 19, Issue 4
            Special Section on Trust and AI and Regular Papers
            November 2019
            201 pages
            ISSN:1533-5399
            EISSN:1557-6051
            DOI:10.1145/3362102
            • Editor:
            • Ling Liu
            Issue’s Table of Contents

            Copyright © 2019 ACM

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            Publication History

            • Published: 19 September 2019
            • Accepted: 1 March 2019
            • Revised: 1 February 2019
            • Received: 1 November 2018
            Published in toit Volume 19, Issue 4

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