  This article reviews the Author-Topic Model and presents a new non-parametric
extension based on the Hierarchical Dirichlet Process. The extension is
especially suitable when no prior information about the number of components
necessary is available. A blocked Gibbs sampler is described and focus put on
staying as close as possible to the original model with only the minimum of
theoretical and implementation overhead necessary.
