This paper’s contribution is placed into decision-making process research area. In our previous papers we showed how decision maker’s behavior can be captured in logs and how an aggregated decision data model (DDM) can be mined. We now introduce two recommendation algorithms that...

The recent decade has witnessed the increasing popularity of recommender systems, which help users acquire relevant commodities and services from overwhelming resources on Internet. Some simple physical diffusion processes have been used to design effective recommendation algorithms for...

In this paper, we propose a influence-based approach to investigate network-based recommendation systems. Different from the previous mass diffusion approach, we give a new expression of initial resource distribution and take into account the influence of resources associated with the receiver...