… , we propose to learn a trust aware item ranking model on multicategory social networks. In
order to learn from implicit feedback, we reconstruct the user-item rating matrix using the data …

… We further assume that users in U are sorted by their status scores S in descending order. …
We use G ∈ Rn×n to denote user-user trust relations where Gij = 1 if ui trusts uj, zero oth…

… social network, and the trust between users is calculated using the Page rank algorithm and
… be seen that this recommendation model obtains higher recommendation model accuracy. …

… This study proposes a bidirectional recommendation model to tackle the user cold start
problem. We can predict the middle item when a user has only a few user-item interactions and …

… new user cold-start recommendations remain a challenge. In this paper, we have developed
… GAN-based recommendation model to address new user cold-start recommendations. The …

… We present a novel two-step algorithm for identifying user correspondence and item correspondence
between two homogeneous rating matrices. We then introduce a simple …

… for predicting trust relations and further building trust networks. In this study, we investigate
whether we can predict trust relations via a sparse learning model, and propose to build a …

… This thesis could assist product or service marketers who use Plurk or similar microblogging
platforms … A novel recommendation model regularized with user trust and item ratings. IEEE …

… with only one topic model might limit performance and interpretation ability of … recommendation
model. Thus we extend the model of Wang and Blei by utilizing multiple topic models…

China's release of a White Paper to document its Arctic Policy in 2018 has attracted widespread
academic and popular commentaries. In particular, Beijing's ambition to build a “Polar …