  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.
