Probabilistic partial knowledge handling Original Research Article

This paper is a short review and comparison of two probabilistic models for uncertain knowledge representation: Bayesian networks and compositional models. We have chosen these two approaches because they represent the same class of distributions and because they are typical representatives of the approaches using conditional (for Bayesian networks) and unconditional (for compositional models) distributions as basic building blocks for model construction.