… Specifically, user trust neighbor set that has similar preference and taste with a target user
is first obtained by trust expansion strategy via user trust diffusion features in a trust network. …

… We validate our recommendation model on two public datasets of item reviews. … For this
purpose, we propose a compositional trust model and recommender system which rely on …

… the users trust different friends on different items, so we integrate the social circle effect
into the recommendation, and then we combine item’s inherent characteristics and popular …

… Reliability measurement is known as one of the important factors used in recommendation
models to determine how much we can trust the recommendations (Hernando, Bobadilla, …

… Improved rating prediction model In order to introduce user trust to improve the rating prediction
model, we define the trusted user feature matrix W M × D . This paper uses an adjacency …

… based on matrix factorization approach which also uses social trust and influence of social
network. TrustSVD [31] regularizes recommendation model with user trust and item ratings. …

… [19] proposed SoRec algorithm, it decomposes the user rating matrix and the user trust
relationship matrix at the same time, and integrates the rating information and social network …

… recommendation model based on user ratings and trust. Then, the user internal factors are
integrated into a MF model to improve the accuracy of rating predictions and alleviate the cold …

… ) algorithm we improved for sparse trust mining. • Through … trust and sparse trust into a
recommendation model can achieve better recommendation effect than incorporating social trust …

… Note that, a higher number of trustors for a trustee shows that more users trust the trustee, …
Yorke-Smith, “A novel recommendation model regularized with user trust and item ratings,” …