Join graph edges in context of algebraic Bayesian network minimal join graph cliques comparative analysis
Andrey Alexandrovich Filchenkov, Alexander Lvovich Tulupyev, Vladimirovich Alexander Sirotkin · Informatics and Automation · 2014
Algebraic Bayesian networks (ABN) are probabilistic-logic graphic models of knowledge systems with uncertainty and gives an advantage to deal with interval probability estimates. Secondary structure usually represented as an join graph is essential for ABN work. The article analyses edges of various minimal join graph cliques to specify different clique types. In particular, it is proven that vertex set of the class of cliques that are basic for minimal join graph set synthesis equals to set of end of specified edges, weight of those equals to the clique weight.