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A Probabilistic Graph Model for Trust Opinion Estimation in Online Social Networks (1909.10055v1)

Published 22 Sep 2019 in cs.SI and physics.soc-ph

Abstract: Trust assessment plays a key role in many online applications, such as online money lending, product reviewing and active friending. Trust models usually employ a group of parameters to represent the trust relation between a trustor-trustee pair. These parameters are originated from the trustor's bias and opinion on the trustee. Naturally, these parameters can be regarded as a vector. To address this problem, we propose a framework to accurately convert the single values to the parameters needed by 3VSL. The framework firstly employs a probabilistic graph model (PGM) to derive the trustor's opinion and bias to his rating on the trustee.

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Authors (2)
  1. Luke Liu (3 papers)
  2. Qing Yang (138 papers)
Citations (1)

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