This article aims to present a set of discourse structure relations that are easy to code and to
develop criteria for an appropriate data structure for representing these relations. Discourse …

This book presents the fundamental concepts of probabilistic graphical models, or
probabilistic networks as they are called in this book. Probabilistic networks have become …

A Markov property associates a set of conditional independencies to a graph. Two
alternative Markov properties are available for chain graphs (CGs), the Lauritzen–Wermuth …

We study criteria for identifiability of path analysis models with one hidden variable. We first
derive sufficient criteria for identification of models in which marginalisation is carried out …

This paper deals with the Intersection Property, or Basu's First Theorem, which is valid under
a condition of no common information, also known as measurable separability. After …

It is well known that there may be many causal explanations that are consistent with a given
set of data. For processes that can be represented by a directed acyclic graph (DAG), many …

Consider a model-based decision support system (DSS) where all the variables involved
are binary, each taking on 0 or 1. The system categorizes the probability that a certain …

The dependence structure of an observed process induced by temporal aggregation of a
time evolving hidden spatial phenomenon is addressed. Data are described by means of …

The question of efficient characterization of inclusion neighbourhood is crucial in some
methods for learning (equivalence classes of) Bayesian networks. In this paper …