We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Abstract. Multiply sectioned Bayesian networks (MSBNs) were originally proposed as a modular representation of uncertain knowledge by sectioning a large Bayesian network (BN) into ...
One fascinating aspect of tool building for datamining is the application of a generalized datamining tool to a specific domain. Often times, this process results in a cross disci...
Andy Novobilski, Francis M. Fesmire, David Sonnema...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...