Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
In this paper, we propose an efficient mechanism dealing with trust assessment for agent societies, aiming to accurately assess the trustworthiness of the collaborating agents. I...
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between us...
Alireza Zarghami, Soude Fazeli, Nima Dokoohaki, Mi...
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...